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**Edge Deployment Frameworks**","Swift"],"sub_categories":["🍎 **CoreML** - Apple"],"readme":"# CoreML-Models\nConverted Core ML Model Zoo.\n\n\u003cimg width=\"1280\" src=\"https://user-images.githubusercontent.com/23278992/147420041-fdeb1fbb-7e93-41c6-84d6-80d7c1c45200.jpeg\"\u003e\n\nCore ML is a machine learning framework by Apple.\nIf you are iOS developer, you can easly use machine learning models in your Xcode project. \n\n# How to use\n\nTake a look this model zoo, and if you found the CoreML model you want,\ndownload the model from google drive link and bundle it in your project.\nOr if the model have sample project link, try it and see how to use the model in the project.\nYou are free to do or not.\n\n**If you like this repository, please give me a star so I can do my best.**\n\n# Section Link\n\n- [**Image Classifier**](#image-classifier)\n  - [Efficientnetb0](#efficientnetb0)\n  - [Efficientnetv2](#efficientnetv2)\n  - [VisionTransformer](#visiontransformer)\n  - [Conformer](#conformer)\n  - [DeiT](#deit)\n  - [RepVGG](#repvgg)\n  - [RegNet](#regnet)\n  - [MobileViTv2](#mobilevitv2)\n\n  \n- [**Object Detection**](#object-detection)\n  - [YOLOv5s](#yolov5s)\n  - [YOLOv7](#yolov7)\n  - [YOLOv8](#yolov8)\n\n- [**Segmentation**](#segmentation)\n  - [U2Net](#u2net)\n  - [IS-Net](#is-net)\n  - [RMBG1.4](#rmbg14)\n  - [face-parsing](#face-parsing)\n  - [Segformer](#segformer)\n  - [BiseNetv2](#bisenetv2)\n  - [DNL](#dnl)\n  - [ISANet](#isanet)\n  - [FastFCN](#fastfcn)\n  - [GCNet](#gcnet)\n  - [DANet](#danet)\n  - [Semantic FPN](#semantic-fpn)\n  - [cloths_segmentation](#cloths_segmentation)\n  - [easyportrait](#easyportrait)\n\n- [**Super Resolution**](#super-resolution)\n  - [Real ESRGAN](#real-esrgan)\n  - [GFPGAN](#gfpgan)\n  - [BSRGAN](#bsrgan)\n  - [A-ESRGAN](#a-esrgan)\n  - [Beby-GAN](#beby-gan)\n  - [RRDN](#rrdn)\n  - [Fast-SRGAN](#fast-srgan)\n  - [ESRGAN](#esrgan)\n  - [UltraSharp](#ultrasharp)\n  - [SRGAN](#srgan)\n  - [SRResNet](#srresnet)\n  - [LESRCNN](#lesrcnn)\n  - [MMRealSR](#mmrealsr)\n  - [DASR](#dasr)\n      \n- [**Low Light Enhancement**](#low-light-enhancement)\n  - [StableLLVE](#stablellve)\n  - [Zero-DCE](#zero-dce)\n  - [Retinexformer](#retinexformer)\n\n- [**Image Restoration**](#image-restroration)\n  - [MPRNet](#mprnet)\n  - [MIRNetv2](#mirnetv2)\n  \n- [**Image Generation**](#image-generation)\n  - [MobileStyleGAN](#mobilestylegan)\n  - [DCGAN](#dcgan)\n\n- [**Image2Image**](#image2image)\n  - [Anime2Sketch](#anime2sketch)\n  - [AnimeGAN2Face_Paint_512_v2](#animegan2face_paint_512_v2)\n  - [Photo2Cartoon](#photo2cartoon)\n  - [AnimeGANv2_Hayao](#animeGANv2_hayao)\n  - [AnimeGANv2_Paprika](#animeGANv2_paprika)\n  - [WarpGAN Caricature](#warpgancaricature)\n  - [UGATIT_selfie2anime](#ugatit_selfie2anime)\n  - [Fast-Neural-Style-Transfer](#fast-neural-style-transfer)\n  - [White_box_Cartoonization](#white_box_cartoonization)\n  - [FacialCartoonization](#facialcartoonization)\n\n- [**Inpainting**](#inpainting)\n  - [AOT-GAN-for-Inpainting](#aot-gan-for-inpainting)\n  - [Lama](#lama)\n\n- [**Monocular Depth Estimation**](#monocular-depth-estimation)\n  - [MiDaS](#midas)\n  \n- [**Stable Diffusion**](#stable-diffusion) **:text2image**\n  - [stable-diffusion-v1-5](#stable-diffusion-v1-5)\n  - [pastel-mix](#pastel-mix)\n  - [Orange Mix](#orange-mix)\n  - [Counterfeit-V2.5](#counterfeit)\n  - [anything-v4.5](#anything-v4)\n  - [Openjourney](#openjourney)\n  - [dreamlike-photoreal-2.0](#dreamlike-photoreal-2)\n\n# How to get the model\nYou can get the model converted to CoreML format from the link of Google drive.\nSee the section below for how to use it in Xcode.\nThe license for each model conforms to the license for the original project.\n\n# Image Classifier\n\n### Efficientnet\n\n\u003cimg width=\"400\" alt=\"スクリーンショット 2021-12-27 6 34 43\" src=\"https://user-images.githubusercontent.com/23278992/147420587-108b87f8-7996-4288-905a-ad53f9142221.png\"\u003e\n\n| Google Drive Link | Size | Dataset |Original Project | License |\n| ------------- | ------------- | ------------- |------------- |------------- |\n| [Efficientnetb0](https://drive.google.com/file/d/1mJq8SMuDaCQHW77ui3fAfe5o3Qu2GKMi/view?usp=sharing) | 22.7 MB | ImageNet | [TensorFlowHub](https://tfhub.dev/tensorflow/efficientnet/b0/classification/1)  |[Apache2.0](https://opensource.org/licenses/Apache-2.0)|\n\n\n### Efficientnetv2\n\n\u003cimg width=\"400\" alt=\"スクリーンショット 2021-12-31 4 30 22\" src=\"https://user-images.githubusercontent.com/23278992/147782567-bbf26186-8c84-4073-8df4-b08e06d4e791.png\"\u003e\n\n| Google Drive Link | Size | Dataset |Original Project | License | Year|\n| ------------- | ------------- | ------------- |------------- |------------- |------------- |\n| [Efficientnetv2](https://drive.google.com/file/d/12JiGwXh8pX3yjoG_GsJOKAnPd3lbVrrn/view?usp=sharing) | 85.8 MB | ImageNet | [Google/autoML](https://github.com/google/automl/tree/master/efficientnetv2)  | [Apache2.0](https://github.com/google/automl/blob/master/LICENSE)|2021|\n\n### VisionTransformer\n\nAn Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.\n\n\u003cimg width=\"400\" alt=\"スクリーンショット 2022-01-07 10 37 05\" src=\"https://user-images.githubusercontent.com/23278992/148482246-64269fb4-fda4-4bd5-b219-5bf860fd77e7.png\"\u003e\n\n| Google Drive Link | Size | Dataset |Original Project | License |Year|\n| ------------- | ------------- | ------------- |------------- |------------- |------------- |\n| [VisionTransformer-B16](https://drive.google.com/file/d/1VPo8Cjv7dyicM4lcJ6TgxnD4AN3ldMQp/view?usp=sharing) | 347.5 MB | ImageNet | [google-research/vision_transformer](https://github.com/google-research/vision_transformer)  | [Apache2.0](https://github.com/google-research/vision_transformer/blob/main/LICENSE)|2021|\n\n### Conformer\n\nLocal Features Coupling Global Representations for Visual Recognition.\n\n\u003cimg width=\"400\" alt=\"スクリーンショット 2022-01-07 11 34 33\" src=\"https://user-images.githubusercontent.com/23278992/148482144-2d5bb7e8-ed67-4146-9f9d-c95fe94735d3.png\"\u003e\n\n| Google Drive Link | Size | Dataset |Original Project | License |Year|\n| ------------- | ------------- | ------------- |------------- |------------- |------------- |\n| [Conformer-tiny-p16](https://drive.google.com/file/d/1-4qVbuTYr4r4o08656iGtV8KKblAVVyr/view?usp=sharing) | 94.1 MB | ImageNet | [pengzhiliang/Conformer](https://github.com/pengzhiliang/Conformer)  | [Apache2.0](https://github.com/google-research/vision_transformer/blob/main/LICENSE)|2021|\n\n### DeiT\n\nData-efficient Image Transformers\n\n\u003cimg width=\"400\" alt=\"スクリーンショット 2022-01-07 11 50 25\" src=\"https://user-images.githubusercontent.com/23278992/148484220-38494287-49b4-4992-9ceb-9dc7b75a250e.png\"\u003e\n\n| Google Drive Link | Size | Dataset |Original Project | License |Year|\n| ------------- | ------------- | ------------- |------------- |------------- |------------- |\n| [DeiT-base384](https://drive.google.com/file/d/1-7J-b0fTjmZi2VDPrDCWKBsCYGxYP5yW/view?usp=sharing) | 350.5 MB | ImageNet | [facebookresearch/deit](https://github.com/facebookresearch/deit)  | [Apache2.0](https://github.com/facebookresearch/deit/blob/main/LICENSE)|2021|\n\n### RepVGG\n\nMaking VGG-style ConvNets Great Again\n\n\u003cimg width=\"400\" alt=\"スクリーンショット 2022-01-08 5 00 53\" src=\"https://user-images.githubusercontent.com/23278992/148600326-69dd9666-2709-4318-914b-30db8c294fd3.png\"\u003e\n\n| Google Drive Link | Size | Dataset |Original Project | License |Year|\n| ------------- | ------------- | ------------- |------------- |------------- |------------- |\n| [RepVGG-A0](https://drive.google.com/file/d/1i8mDvRGn2_OjzIG9ioVJyQrefVliKsh_/view?usp=sharing) | 33.3 MB | ImageNet | [DingXiaoH/RepVGG](https://github.com/DingXiaoH/RepVGG)  | [MIT](https://github.com/DingXiaoH/RepVGG/blob/main/LICENSE)|2021|\n\n### RegNet\n\nDesigning Network Design Spaces\n\n\u003cimg width=\"400\" alt=\"スクリーンショット 2022-02-23 7 38 23\" src=\"https://user-images.githubusercontent.com/23278992/155233183-edf61ebe-922c-4b63-8a5e-7ef6c9f7eaa8.png\"\u003e\n\n| Google Drive Link | Size | Dataset |Original Project | License |Year|\n| ------------- | ------------- | ------------- |------------- |------------- |------------- |\n| [regnet_y_400mf](https://drive.google.com/file/d/16jbUJ4gHSzdxxbYb99rOQe0FiKCuLyDB/view?usp=sharing) | 16.5 MB | ImageNet | [TORCHVISION.MODELS](https://pytorch.org/vision/stable/models.html#torchvision-models)  | [MIT](https://github.com/facebookresearch/pycls/blob/main/LICENSE)|2020|\n\n\n### MobileViTv2\n\nCVNets: A library for training computer vision networks\n\n\u003cimg width=\"400\" alt=\"スクリーンショット 2022-02-23 7 38 23\" src=\"https://user-images.githubusercontent.com/23278992/225600794-a0a4dc00-cc67-4614-82ed-3ed8633cf03e.png\"\u003e\n\n| Google Drive Link | Size | Dataset |Original Project | License |Year|Conversion Script|\n| ------------- | ------------- | ------------- |------------- |------------- |------------- |------------- |\n| [MobileViTv2](https://drive.google.com/file/d/1__aG67p6o5-NIchkHpfFJBszCpIhI0uf/view?usp=share_link) | 18.8 MB | ImageNet | [apple/ml-cvnets](https://github.com/apple/ml-cvnets)  | [apple](https://github.com/apple/ml-cvnets/blob/main/LICENSE)|2022|[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)]([https://colab.research.google.com/drive/1QiTlFsN948Xt2e4WgqUB8DnGgwWwtVZS?usp=sharing](https://colab.research.google.com/drive/1UQwhFpVP_4Q9I6LXPdBSS0VDhIRdUBQA?usp=sharing)) |\n\n# Object Detection\n\n### YOLOv5s\n\n\u003cimg width=\"400\" alt=\"スクリーンショット 2021-12-29 6 17 08\" src=\"https://user-images.githubusercontent.com/23278992/147608051-be2ff345-22e8-4f82-83ed-7cc41ce4084d.png\"\u003e\n\n| Google Drive Link | Size | Output | Original Project | License | Note | Sample Project |\n| ------------- | ------------- | ------------- | ------------- |------------- |------------- |------------- |\n|[YOLOv5s](https://drive.google.com/file/d/1KT-9eKO4F-LYIJVYJg7dy2LEW_hVUq0M/view?usp=sharing)|29.3MB| Confidence(MultiArray (Double 0 × 80)), Coordinates (MultiArray (Double 0 × 4)) |[ultralytics/yolov5](https://github.com/ultralytics/yolov5)|[GNU](https://github.com/ultralytics/yolov5/blob/master/LICENSE)|Non Maximum Suppression has been added.| [CoreML-YOLOv5](https://github.com/john-rocky/CoreML-YOLOv5) |\n\n### YOLOv7\n\n\u003cimg width=\"400\" alt=\"スクリーンショット 2021-12-29 6 17 08\" src=\"https://user-images.githubusercontent.com/23278992/178128011-e0056777-0c2a-495b-b132-7741cc693077.png\"\u003e\n\n| Google Drive Link | Size | Output | Original Project | License | Note | Sample Project | Conversion Script |\n| ------------- | ------------- | ------------- | ------------- |------------- |------------- |------------- |------------- |\n|[YOLOv7](https://drive.google.com/file/d/1EKBC7tiwP1tDvXUm_ldD1Nq7hW8HofLe/view?usp=sharing)|147.9MB| Confidence(MultiArray (Double 0 × 80)), Coordinates (MultiArray (Double 0 × 4)) |[WongKinYiu/yolov7](https://github.com/WongKinYiu/yolov7)|[GNU](https://github.com/WongKinYiu/yolov7/blob/main/LICENSE.md)|Non Maximum Suppression has been added.| [CoreML-YOLOv5](https://github.com/john-rocky/CoreML-YOLOv5) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1QiTlFsN948Xt2e4WgqUB8DnGgwWwtVZS?usp=sharing) |\n\n### YOLOv8\n\n\u003cimg width=\"400\" alt=\"スクリーンショット 2021-12-29 6 17 08\" src=\"https://user-images.githubusercontent.com/23278992/211807010-d48854b3-beb0-46a8-bd99-cbb9351529b0.png\"\u003e\n\n| Google Drive Link | Size | Output | Original Project | License | Note | Sample Project | \n| ------------- | ------------- | ------------- | ------------- |------------- |------------- |------------- |\n|[YOLOv8s](https://drive.google.com/file/d/1pLRh1Y37KLEMpQn3v8qH-A12swakoHbI/view?usp=share_link)|45.1MB| Confidence(MultiArray (Double 0 × 80)), Coordinates (MultiArray (Double 0 × 4)) |[ultralytics/ultralytics](https://github.com/ultralytics/ultralytics)|[GNU](https://github.com/ultralytics/ultralytics/blob/main/LICENSE)|Non Maximum Suppression has been added.| [CoreML-YOLOv5](https://github.com/john-rocky/CoreML-YOLOv5) |\n\n# Segmentation\n\n### [U2Net](https://drive.google.com/file/d/1cpm-x12Ih7Cqd_kOjfTvtt4ipGS3BpCx/view?usp=sharing)\n\u003cimg width=\"400\" src=\"https://camo.qiitausercontent.com/a8e89c72c0950db66d63415b9010d203aae22617/68747470733a2f2f71696974612d696d6167652d73746f72652e73332e61702d6e6f727468656173742d312e616d617a6f6e6177732e636f6d2f302f3233353235392f36303037393162322d633534332d613537652d303639622d3863663130373932643662392e6a706567\"\u003e \u003cimg width=\"400\" src=\"https://camo.qiitausercontent.com/4f502487cd9e9e02d150ad63b33683a1446e7516/68747470733a2f2f71696974612d696d6167652d73746f72652e73332e61702d6e6f727468656173742d312e616d617a6f6e6177732e636f6d2f302f3233353235392f39636532633237612d643134322d663136352d343365662d6532373966646337386333382e706e67\"\u003e\n\n| Google Drive Link | Size | Output |Original Project | License |\n| ------------- | ------------- | ------------- | ------------- |------------- |\n| [U2Net](https://drive.google.com/file/d/1cpm-x12Ih7Cqd_kOjfTvtt4ipGS3BpCx/view?usp=sharing) | 175.9 MB | Image(GRAYSCALE 320 × 320)| [xuebinqin/U-2-Net](https://github.com/xuebinqin)  | [Apache](https://github.com/john-rocky/CoreML-Models/blob/master/Apache-LICENSE)|\n| [U2Netp](https://drive.google.com/file/d/1D-quPGy33PzSEC6A7EBNv7mCyuiBlO08/view?usp=sharing) | 4.6 MB | Image(GRAYSCALE 320 × 320) | [xuebinqin/U-2-Net](https://github.com/xuebinqin)  |  [Apache](https://github.com/john-rocky/CoreML-Models/blob/master/Apache-LICENSE)|\n\n### [IS-Net](https://drive.google.com/drive/folders/13CkOTBCYc3FjGTU26lmCsRYsOkeHnAMA?usp=sharing)\n\u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/179818731-b919c8a2-f5c9-4a80-8666-e3034d1e86f0.jpg\"\u003e \u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/179818740-38336aec-c9c5-4471-b529-ae45286062b5.JPG\"\u003e\n\u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/186722092-3b8ed1a1-4a03-4357-9bfd-9ec213e7d87d.jpeg\"\u003e \u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/186791654-42b4ba54-f06f-43d3-805b-5bb89e5df272.JPG\"\u003e\n\n| Google Drive Link | Size | Output |Original Project | License | Year | Conversion Script |\n| ------------- | ------------- | ------------- | ------------- |------------- | ------------- |------------- |\n| [IS-Net](https://drive.google.com/drive/folders/13CkOTBCYc3FjGTU26lmCsRYsOkeHnAMA?usp=sharing) | 176.1 MB | Image(GRAYSCALE 1024 × 1024)| [xuebinqin/DIS](https://github.com/xuebinqin/DIS)  | [Apache](https://github.com/xuebinqin/DIS/blob/main/LICENSE.md)| 2022 |[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1xWD7LZbI-_09LXmiYMdhA28V2qujvOlZ?usp=sharing)|\n| [IS-Net-General-Use](https://drive.google.com/file/d/1Vglh1zPwTglroMvycnkLdFP6nCHf_GuH/view?usp=sharing) | 176.1 MB | Image(GRAYSCALE 1024 × 1024)| [xuebinqin/DIS](https://github.com/xuebinqin/DIS)  | [Apache](https://github.com/xuebinqin/DIS/blob/main/LICENSE.md)| 2022 |[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1xWD7LZbI-_09LXmiYMdhA28V2qujvOlZ?usp=sharing)|\n\n### RMBG1.4\n\nRMBG1.4 - The IS-Net enhanced with our unique training scheme and proprietary dataset. \n\n\u003cimg src=\"https://github.com/john-rocky/PersonSegmentationSampler/assets/23278992/2a91ec10-fe94-43be-aedc-283e71fa9a1e\" width=400\u003e \u003cimg src=\"https://github.com/john-rocky/PersonSegmentationSampler/assets/23278992/04af501d-996d-48f4-b008-f0076dcbc117\" width=400\u003e\n\n| Google Drive Link | Size | Output |Original Project | License | year  |Conversion Script |\n| ------------- | ------------- | ------------- |------------- | ------------- | ------------- |------------- |\n| [RMBG.mlpackage](https://drive.google.com/drive/folders/1-33OTxUoO6en8sVsFEvt3Vt_FQ-hwJ3m?usp=sharing)/[RMBG.mlmodel](https://drive.google.com/file/d/1-_O7uLioAvi9q0wbJOiis0dqa8ho4A4o/view?usp=drive_link) | 176 MB | Image(GrayScale 1024x1024) |[briaai/RMBG-1.4](https://huggingface.co/briaai/RMBG-1.4) | [Creative Commons](https://huggingface.co/briaai/RMBG-1.4) |2024|[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1KUTREfLbDklnKhaaJU2Q444TLxjmIXwN?usp=sharing)|\n\n### face-Parsing\n\n\u003cimg src=\"https://user-images.githubusercontent.com/23278992/147860040-14a7e022-5490-4e51-98cd-cd421066dd8c.png\" width=400\u003e \u003cimg src=\"https://user-images.githubusercontent.com/23278992/147860042-d27f37b0-227b-45ab-8d76-f6c6f2f5b3a4.png\" width=400\u003e\n\n| Google Drive Link | Size | Output |Original Project | License | Sample Project |\n| ------------- | ------------- | ------------- | ------------- | ------------- | ------------- |\n| [face-Parsing](https://drive.google.com/file/d/1I_cu8x0k6d1AEV_VPLyMu3Pqg3hwmo7g/view?usp=sharing) | 53.2 MB | MultiArray(1 x 512 × 512)| [zllrunning/face-parsing.PyTorch](https://github.com/zllrunning/face-parsing.PyTorch)  | [MIT](https://github.com/zllrunning/face-parsing.PyTorch/blob/master/LICENSE)|[CoreML-face-parsing](https://github.com/john-rocky/CoreML-Face-Parsing) |\n\n### Segformer\n\nSimple and Efficient Design for Semantic Segmentation with Transformers\n\n\u003cimg src=\"https://user-images.githubusercontent.com/23278992/148621010-5ecf6b90-c501-4cf8-91e1-446850030265.png\" width=400\u003e \u003cimg src=\"https://user-images.githubusercontent.com/23278992/148621013-44d9cd29-ef3c-4250-bbd9-4e4093385a54.JPG\" width=400\u003e\n\n| Google Drive Link | Size | Output |Original Project | License | year |\n| ------------- | ------------- | ------------- | ------------- | ------------- | ------------- |\n| [SegFormer_mit-b0_1024x1024_cityscapes](https://drive.google.com/file/d/1-lcNjJM85DZh5-xQv4jlKL6I1ZMBk2uu/view?usp=sharing) | 14.9 MB | MultiArray(512 × 1024)| [NVlabs/SegFormer](https://github.com/NVlabs/SegFormer)  | [NVIDIA](https://github.com/NVlabs/SegFormer/blob/master/LICENSE)|2021|\n\n### BiSeNetV2\t\n\nBilateral Network with Guided Aggregation for Real-time Semantic Segmentation\n\n\u003cimg src=\"https://user-images.githubusercontent.com/23278992/148663182-c1f3b9dd-8db4-49be-bf92-97a898a8b477.jpg\" width=400\u003e \u003cimg src=\"https://user-images.githubusercontent.com/23278992/148663183-327dc684-342d-43f1-a8d8-ebf817c91bdd.JPG\" width=400\u003e\n\n| Google Drive Link | Size | Output |Original Project | License | year |\n| ------------- | ------------- | ------------- | ------------- | ------------- | ------------- |\n| [BiSeNetV2_1024x1024_cityscapes](https://drive.google.com/file/d/1-20x0-TP8zqXCzDhH06TyL03SJRFYY9n/view?usp=sharing) | 12.8 MB | MultiArray | [ycszen/BiSeNet](https://github.com/ycszen/BiSeNet)  | Apache2.0 |2021|\n\n### DNL\n\nDisentangled Non-Local Neural Networks\n\n\u003cimg src=\"https://user-images.githubusercontent.com/23278992/150061280-23a1de7c-2e12-41d2-9056-7c4b375193a6.jpg\" width=400\u003e \u003cimg src=\"https://user-images.githubusercontent.com/23278992/150061290-eed50b79-f5c0-4fa4-b5bf-728b9029f34c.png\" width=400\u003e\n\n| Google Drive Link | Size | Output |Dataset|Original Project | License | year |\n| ------------- | ------------- | ------------- |------------- | ------------- | ------------- | ------------- |\n| [dnl_r50-d8_512x512_80k_ade20k](https://drive.google.com/file/d/1DOnPGocotsjXknBuNqikgpFVpmH6s_E3/view?usp=sharing) | 190.8 MB | MultiArray[512x512] |ADE20K| [yinmh17/DNL-Semantic-Segmentation](https://github.com/yinmh17/DNL-Semantic-Segmentation)  | [Apache2.0](https://github.com/yinmh17/DNL-Semantic-Segmentation/blob/master/LICENSE) |2020|\n\n### ISANet\n\nInterlaced Sparse Self-Attention for Semantic Segmentation\n\n\u003cimg src=\"https://user-images.githubusercontent.com/23278992/150234575-7dcb8521-4ebd-46aa-bd19-4c1036b514dc.jpg\" width=400\u003e \u003cimg src=\"https://user-images.githubusercontent.com/23278992/150234561-41478d2a-b411-48df-9980-8553c381e530.png\" width=400\u003e\n\n| Google Drive Link | Size | Output |Dataset|Original Project | License | year |\n| ------------- | ------------- | ------------- |------------- | ------------- | ------------- | ------------- |\n| [isanet_r50-d8_512x512_80k_ade20k](https://drive.google.com/file/d/114ypGU9S1BOT2otl7P_gsmZbA3bCmz5K/view?usp=sharing) | 141.5 MB | MultiArray[512x512] |ADE20K| [openseg-group/openseg.pytorch](https://github.com/openseg-group/openseg.pytorch) | [MIT](https://github.com/openseg-group/openseg.pytorch/blob/master/LICENSE) |ArXiv'2019/IJCV'2021|\n\n### FastFCN\n\nRethinking Dilated Convolution in the Backbone for Semantic Segmentation\n\n\u003cimg src=\"https://user-images.githubusercontent.com/23278992/150237380-3b8522e6-e310-436e-b5c3-60b7ff8cb606.jpg\" width=400\u003e \u003cimg src=\"https://user-images.githubusercontent.com/23278992/150237372-1d17f4e2-cf1b-49f0-82b8-d9e6644ff465.png\" width=400\u003e\n\n| Google Drive Link | Size | Output |Dataset|Original Project | License | year |\n| ------------- | ------------- | ------------- |------------- | ------------- | ------------- | ------------- |\n| [fastfcn_r50-d32_jpu_aspp_512x512_80k_ade20k](https://drive.google.com/file/d/1-2CUR1M-a4xzUxdf5enU_9cUdxONmFbT/view?usp=sharing) | 326.2 MB | MultiArray[512x512] |ADE20K| [wuhuikai/FastFCN](https://github.com/wuhuikai/FastFCN) | [MIT](https://github.com/wuhuikai/FastFCN/blob/master/LICENSE) |ArXiv'2019|\n\n### GCNet\n\nNon-local Networks Meet Squeeze-Excitation Networks and Beyond\n\n\u003cimg src=\"https://user-images.githubusercontent.com/23278992/150239404-9d6438ec-cee5-44b9-9179-436ac5ceaab2.jpg\" width=400\u003e \u003cimg src=\"https://user-images.githubusercontent.com/23278992/150239421-cceaae77-eb6b-468d-a069-72750fc6b0f4.png\" width=400\u003e\n\n| Google Drive Link | Size | Output |Dataset|Original Project | License | year |\n| ------------- | ------------- | ------------- |------------- | ------------- | ------------- | ------------- |\n| [gcnet_r50-d8_512x512_20k_voc12aug](https://drive.google.com/file/d/1-DfjorbUDFXOVasSPoGk7GP1XC_OnNVT/view?usp=sharing) | 189 MB | MultiArray[512x512] |PascalVOC| [xvjiarui/GCNet](https://github.com/xvjiarui/GCNet) | [Apache License 2.0](https://github.com/xvjiarui/GCNet/blob/master/LICENSE) |ICCVW'2019/TPAMI'2020|\n\n### DANet\n\nDual Attention Network for Scene Segmentation(CVPR2019)\n\n\u003cimg src=\"https://user-images.githubusercontent.com/23278992/150419837-980a0e0f-6333-4853-b638-6e6854e093e3.jpg\" width=400\u003e \u003cimg src=\"https://user-images.githubusercontent.com/23278992/150419740-052fca9b-0519-440c-bffd-5abc7a5ac240.png\" width=400\u003e\n\n| Google Drive Link | Size | Output |Dataset|Original Project | License | year |\n| ------------- | ------------- | ------------- |------------- | ------------- | ------------- | ------------- |\n| [danet_r50-d8_512x1024_40k_cityscapes](https://drive.google.com/file/d/1A45r_725V7edPTSrjA4T-T03rPD6Sj2z/view?usp=sharing) | 189.7 MB | MultiArray[512x1024] |CityScapes| [junfu1115/DANet](https://github.com/junfu1115/DANet/) | [MIT](https://github.com/junfu1115/DANet/blob/master/LICENSE) |CVPR2019|\n\n### Semantic-FPN\n\nPanoptic Feature Pyramid Networks\n\n\u003cimg src=\"https://user-images.githubusercontent.com/23278992/150614015-6b712113-6b8f-484e-88dc-124b76229153.jpg\" width=400\u003e \u003cimg src=\"https://user-images.githubusercontent.com/23278992/150614022-590eb6fa-075f-4ff7-8ad5-b9d502b8763b.png\" width=400\u003e\n\n| Google Drive Link | Size | Output |Dataset|Original Project | License | year |\n| ------------- | ------------- | ------------- |------------- | ------------- | ------------- | ------------- |\n| [fpn_r50_512x1024_80k_cityscapes](https://drive.google.com/file/d/1_IVhCnJ--54P7qVGLo8-ks_LRGXJQXht/view?usp=sharing) | 108.6 MB | MultiArray[512x1024] |CityScapes| [facebookresearch/detectron2](https://github.com/facebookresearch/detectron2) | [Apache License 2.0](https://github.com/facebookresearch/detectron2/blob/main/LICENSE) |2019|\n\n### cloths_segmentation\n\nCode for binary segmentation of various cloths.\n\n\u003cimg src=\"https://user-images.githubusercontent.com/23278992/154873792-54c12be0-d446-4789-bf00-bb89cab5a566.jpg\" width=400\u003e \u003cimg src=\"https://user-images.githubusercontent.com/23278992/154873786-2b90e0d9-dd86-4397-8977-ea1464ca2f75.JPG\" width=400\u003e\n\n| Google Drive Link | Size | Output |Dataset|Original Project | License | year |\n| ------------- | ------------- | ------------- |------------- | ------------- | ------------- | ------------- |\n| [clothSegmentation](https://drive.google.com/file/d/1-2AydEgkth6UTD5bu13R0fJYoqZZMG3e/view?usp=sharing) | 50.1 MB | Image(GrayScale 640x960) |[fashion-2019-FGVC6](https://www.kaggle.com/c/imaterialist-fashion-2019-FGVC6)| [facebookresearch/detectron2](https://github.com/facebookresearch/detectron2) | [MIT](https://github.com/ternaus/cloths_segmentation/blob/main/LICENSE) |2020|\n\n### easyportrait\n\nEasyPortrait - Face Parsing and Portrait Segmentation Dataset.\n\n\u003cimg src=\"https://github.com/john-rocky/CoreML-Models/assets/23278992/6ab8ed6a-2de7-43fd-bb84-2fb77286bd6c\" width=400\u003e \u003cimg src=\"https://github.com/john-rocky/CoreML-Models/assets/23278992/a0b8e435-d04e-4a88-940b-bd5fb45cbc15\" width=400\u003e\n\n| Google Drive Link | Size | Output |Original Project | License | year | Swift sample |Conversion Script |\n| ------------- | ------------- | ------------- |------------- | ------------- | ------------- |------------- |------------- |\n| [easyportrait-segformer512-fp](https://drive.google.com/drive/folders/13BUhNpQHodAgcj6eJaPbzuSUaFn3JuU-?usp=sharing) | 7.6 MB | Image(GrayScale 512x512) * 9 |[hukenovs/easyportrait](https://github.com/hukenovs/easyportrait) | [Creative Commons](https://github.com/hukenovs/easyportrait/tree/main/license) |2023|[easyportrait-coreml](https://github.com/john-rocky/easyportrait-coreml)|[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/11a3XWFA8fa8V0a2zgWFqOMUaZgF4O1qt?usp=sharing)|\n\n# Super Resolution\n\n### [Real ESRGAN](https://drive.google.com/file/d/1cpm-x12Ih7Cqd_kOjfTvtt4ipGS3BpCx/view?usp=sharing)\n\u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/147418147-47f2089f-80ea-4688-ac06-7d9c4b46a08e.png\"\u003e \u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/147418143-b8f89073-afa1-4c5c-95e9-2ee8a00a94b9.JPG\"\u003e \n\n| Google Drive Link | Size | Output |Original Project | License | year |\n| ------------- | ------------- | ------------- | ------------- | ------------- |------------- |\n| [Real ESRGAN4x](https://drive.google.com/file/d/16JEWh48fgQc8az7avROePOd-PYda0Yi2/view?usp=sharing) | 66.9 MB | Image(RGB 2048x2048)| [xinntao/Real-ESRGAN](https://github.com/xinntao/Real-ESRGAN)  | [BSD 3-Clause License](https://github.com/xinntao/Real-ESRGAN/blob/master/LICENSE) |2021|\n| [Real ESRGAN Anime4x](https://drive.google.com/file/d/1qXdLx46Lpqya7Txc5Wvgkd2Dqlnqm3Qm/view?usp=sharing) | 66.9 MB | Image(RGB 2048x2048)| [xinntao/Real-ESRGAN](https://github.com/xinntao/Real-ESRGAN)  | [BSD 3-Clause License](https://github.com/xinntao/Real-ESRGAN/blob/master/LICENSE) |2021|\n\n### [GFPGAN](https://drive.google.com/file/d/1-3fF4aPnh8ygUOmKItIrZ318xI9JGmQx/view?usp=sharing)\n\nTowards Real-World Blind Face Restoration with Generative Facial Prior\n\n\u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/186315786-56634605-e357-4e9e-a0d9-51bb526bf69f.png\"\u003e \u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/186316328-1fc64a6f-a443-4df2-bb86-0af343cd8a64.png\"\u003e \n\n| Google Drive Link | Size | Output |Original Project | License |year |\n| ------------- | ------------- | ------------- | ------------- | ------------- |------------- |\n| [GFPGAN](https://drive.google.com/file/d/1-3fF4aPnh8ygUOmKItIrZ318xI9JGmQx/view?usp=sharing) | 337.4 MB | Image(RGB 512x512)| [TencentARC/GFPGAN](https://github.com/TencentARC/GFPGAN)  | [Apache2.0](https://github.com/TencentARC/GFPGAN/blob/master/LICENSE) |2021|\n\n### [BSRGAN](https://drive.google.com/file/d/1-3K89vJZ5OUAh4xdSAifgnL52jbl2fVf/view?usp=sharing)\n\u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/148810656-4c5faa33-1be9-45f6-b31a-defd931cb1f8.jpg\"\u003e \u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/148811822-56844bc7-b197-44d5-8454-757890c890b5.jpg\"\u003e \n\n| Google Drive Link | Size | Output |Original Project | License |year |\n| ------------- | ------------- | ------------- | ------------- | ------------- |------------- |\n| [BSRGAN](https://drive.google.com/file/d/1-3K89vJZ5OUAh4xdSAifgnL52jbl2fVf/view?usp=sharing) | 66.9 MB | Image(RGB 2048x2048)| [cszn/BSRGAN](https://github.com/cszn/BSRGAN)  |  |2021|\n\n### [A-ESRGAN](https://drive.google.com/file/d/1-0rKVQtFXNWfIBIpvyemjuO3O00GZBeb/view?usp=sharing)\n\u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/151077592-a993a19c-8a05-471a-8924-c7302f7af84b.png\"\u003e \u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/151077667-62bdbe2b-8e00-4816-945a-14890ccf1bcd.png\"\u003e \n\n| Google Drive Link | Size | Output |Original Project | License |year |Conversion Script|\n| ------------- | ------------- | ------------- | ------------- | ------------- |------------- |------------- |\n| [A-ESRGAN](https://drive.google.com/file/d/1-0rKVQtFXNWfIBIpvyemjuO3O00GZBeb/view?usp=sharing) | 63.8 MB | Image(RGB 1024x1024)| [aesrgan/A-ESRGANN](https://github.com/aesrgan/A-ESRGAN)  | [BSD 3-Clause License](https://github.com/aesrgan/A-ESRGAN/blob/main/LICENSE) |2021|[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1UxtSXnVYOXEfTVdIeoP7HQEjsyVbqOKa?usp=sharing)|\n\n### [Beby-GAN](https://drive.google.com/file/d/1bJ7_NgR2KXI46JiFk5hH_6IdCHMyhN05/view?usp=sharing)\n\nBest-Buddy GANs for Highly Detailed Image Super-Resolution\n\n\u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/151282027-14a5d386-60a8-4152-bff1-a0416db81d7a.jpg\"\u003e \u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/151282014-1177b73d-a2b3-40eb-9a87-9cbe8ace504b.jpg\"\u003e \n\n| Google Drive Link | Size | Output |Original Project | License |year |\n| ------------- | ------------- | ------------- | ------------- | ------------- |------------- |\n| [Beby-GAN](https://drive.google.com/file/d/1bJ7_NgR2KXI46JiFk5hH_6IdCHMyhN05/view?usp=sharing) | 66.9 MB | Image(RGB 2048x2048)| [dvlab-research/Simple-SR](https://github.com/dvlab-research/Simple-SR)  | [MIT](https://github.com/dvlab-research/Simple-SR/blob/master/LICENSE) |2021|\n\n### [RRDN](https://drive.google.com/file/d/1-M30vR0xMuYDn2p5O4KZrUnUXy4SNThF/view?usp=sharing)\n\nThe Residual in Residual Dense Network for image super-scaling.\n\n\u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/152622988-795c1279-43f7-4d8a-a2ea-a786bcd6a34b.png\"\u003e \u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/152622984-fbc911c5-901c-4ce3-93b6-753f35dea531.png\"\u003e\n\n| Google Drive Link | Size | Output |Original Project | License |year |\n| ------------- | ------------- | ------------- | ------------- | ------------- |------------- |\n| [RRDN](https://drive.google.com/file/d/1-M30vR0xMuYDn2p5O4KZrUnUXy4SNThF/view?usp=sharing) | 16.8 MB | Image(RGB 2048x2048)| [idealo/image-super-resolution](https://github.com/idealo/image-super-resolution)  | [Apache2.0](https://github.com/idealo/image-super-resolution/blob/master/LICENSE) |2018|\n\n\n### [Fast-SRGAN](https://drive.google.com/file/d/1gYXbhcSUm5rhcCAmwLruonAhu8jvyDL8/view?usp=sharing)\n\nFast-SRGAN.\n\n\u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/156285673-a6239cec-41ec-46d8-a2fa-d0ad21498f1d.png\"\u003e \u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/156285686-8d0333a2-b07f-4aa2-8a44-fe959758289f.png\"\u003e\n\n| Google Drive Link | Size | Output |Original Project | License |year |\n| ------------- | ------------- | ------------- | ------------- | ------------- |------------- |\n| [Fast-SRGAN](https://drive.google.com/file/d/1gYXbhcSUm5rhcCAmwLruonAhu8jvyDL8/view?usp=sharing) | 628 KB | Image(RGB 1024x1024)| [HasnainRaz/Fast-SRGAN](https://github.com/HasnainRaz/Fast-SRGAN)  | [MIT](https://github.com/HasnainRaz/Fast-SRGAN/blob/master/LICENSE) |2019|\n\n### [ESRGAN](https://drive.google.com/file/d/1fkRbh_gckuFlgr357OIdOrEJK4T_2Xkz/view?usp=sharing)\n\nEnhanced-SRGAN.\n\n\u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/156899173-bdc1ceed-c3f6-4abd-b217-18667fc88cf6.jpg\"\u003e \u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/156899267-65343f4e-a963-4680-83ba-7ecd7e6680a5.jpg\"\u003e\n\n| Google Drive Link | Size | Output |Original Project | License |year |\n| ------------- | ------------- | ------------- | ------------- | ------------- |------------- |\n| [ESRGAN](https://drive.google.com/file/d/1fkRbh_gckuFlgr357OIdOrEJK4T_2Xkz/view?usp=sharing) | 66.9 MB | Image(RGB 2048x2048)| [xinntao/ESRGAN](https://github.com/xinntao/ESRGAN)  | [Apache 2.0](https://github.com/xinntao/ESRGAN/blob/master/LICENSE) |2018|\n\n### [UltraSharp](https://drive.google.com/drive/folders/1-Q1SdS8iHWTfTs7FE39pUTEubPks30Ca?usp=drive_link)\n\nPretrained: 4xESRGAN\n\n\u003cimg width=\"400\" src=\"https://github.com/john-rocky/PersonSegmentationSampler/assets/23278992/b98ab056-23b0-486e-a52c-a88e857c1048\"\u003e \u003cimg width=\"400\" src=\"https://github.com/john-rocky/PersonSegmentationSampler/assets/23278992/d4214ded-c9d2-4f18-8de3-222f912862b0\"\u003e\n\n| Google Drive Link | Size | Output |Original Project | License |year |\n| ------------- | ------------- | ------------- | ------------- | ------------- |------------- |\n| [UltraSharp](https://drive.google.com/drive/folders/1-Q1SdS8iHWTfTs7FE39pUTEubPks30Ca?usp=drive_link) | 34 MB | Image(RGB 1024x1024)| [Kim2019/](https://openmodeldb.info/models/4x-UltraSharp)  | [CC-BY-NC-SA-4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/deed.ja) |2021|\n\n### [SRGAN](https://drive.google.com/file/d/1-076W2o0wCtoODptikX1eOnlFBx2s3qK/view?usp=sharing)\n\nPhoto-Realistic Single Image Super-Resolution Using a Generative Adversarial Network.\n\n\u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/156899475-172b7ac5-a6ca-4b0b-a6d8-f0d0ddea986e.png\"\u003e \u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/156899476-641af271-9b2e-4122-a048-099700d8335a.png\"\u003e\n\n| Google Drive Link | Size | Output |Original Project | License |year |\n| ------------- | ------------- | ------------- | ------------- | ------------- |------------- |\n| [SRGAN](https://drive.google.com/file/d/1-076W2o0wCtoODptikX1eOnlFBx2s3qK/view?usp=sharing) | 6.1 MB | Image(RGB 2048x2048)| [dongheehand/SRGAN-PyTorch](https://github.com/dongheehand/SRGAN-PyTorch)  |  |2017|\n\n### [SRResNet](https://drive.google.com/file/d/1-2kYZgF_Z6vntrRsHmRiwyHJg5TC1PSW/view?usp=sharing)\n\nPhoto-Realistic Single Image Super-Resolution Using a Generative Adversarial Network.\n\n\u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/156899905-40746d09-4580-4e30-b0b4-b146fd1975c2.png\"\u003e \u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/156899906-ab5c8c4e-54af-4d55-874b-5d1e0aac961f.JPG\"\u003e\n\n| Google Drive Link | Size | Output |Original Project | License |year |\n| ------------- | ------------- | ------------- | ------------- | ------------- |------------- |\n| [SRResNet](https://drive.google.com/file/d/1-2kYZgF_Z6vntrRsHmRiwyHJg5TC1PSW/view?usp=sharing) | 6.1 MB | Image(RGB 2048x2048)| [dongheehand/SRGAN-PyTorch](https://github.com/dongheehand/SRGAN-PyTorch)  |  |2017|\n\n### [LESRCNN](https://drive.google.com/file/d/1-0zgxURZwqX0mAAVy69K-owE7QP-7NfJ/view?usp=sharing)\n\nLightweight Image Super-Resolution with Enhanced CNN.\n\n\u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/180625941-3a6b44a6-35e1-4ff9-a85b-c5efc81fc101.jpg\"\u003e \u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/180625939-308f7176-488a-40a1-ab6e-428dc01bbf67.jpg\"\u003e\n\n| Google Drive Link | Size | Output |Original Project | License |year | Conversion Script |\n| ------------- | ------------- | ------------- | ------------- | ------------- |------------- |------------- |\n| [LESRCNN](https://drive.google.com/file/d/1-0zgxURZwqX0mAAVy69K-owE7QP-7NfJ/view?usp=sharing) | 4.3 MB | Image(RGB 512x512)| [hellloxiaotian/LESRCNN](https://github.com/hellloxiaotian/LESRCNN)  |  |2020|[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1Q6piAJvXSmb-DcdFipcRUEYuHi9fnTm7?usp=sharing)|\n\n### [MMRealSR](https://drive.google.com/file/d/1-HwMLvOy_hHycHNhojob6uT8t6tRyWqb/view?usp=sharing)\n\nMetric Learning based Interactive Modulation for Real-World Super-Resolution\n\n\u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/186336018-9c5d5700-28a7-438e-bc07-5ca2a8e843cd.png\"\u003e \u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/186336038-5e877d1a-33b1-4f54-9e4d-192f9bb765fe.png\"\u003e\n\n| Google Drive Link | Size | Output |Original Project | License |year | Conversion Script |\n| ------------- | ------------- | ------------- | ------------- | ------------- |------------- |------------- |\n| [MMRealSRGAN](https://drive.google.com/file/d/1-HwMLvOy_hHycHNhojob6uT8t6tRyWqb/view?usp=sharing) | 104.6 MB | Image(RGB 1024x1024)| [TencentARC/MM-RealSR](https://github.com/TencentARC/MM-RealSR)  | [BSD 3-Clause](https://github.com/TencentARC/MM-RealSR/blob/main/LICENSE) |2022|[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1zhUhQhdtP02N2pFIxsO5lin7tDOExZCo?usp=sharing)|\n| [MMRealSRNet](https://drive.google.com/file/d/1-77P8AtHFh5kca2kYZ6X7GaUueoa3el_/view?usp=sharing) | 104.6 MB | Image(RGB 1024x1024)| [TencentARC/MM-RealSR](https://github.com/TencentARC/MM-RealSR)  | [BSD 3-Clause](https://github.com/TencentARC/MM-RealSR/blob/main/LICENSE) |2022|[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1zhUhQhdtP02N2pFIxsO5lin7tDOExZCo?usp=sharing)|\n\n### [DASR](https://drive.google.com/drive/folders/10J2ehHewK2ppS5ToDqmtJ2Ei5k8vcdL0?usp=sharing)\n\nPytorch implementation of \"Unsupervised Degradation Representation Learning for Blind Super-Resolution\", CVPR 2021\n\n\u003cimg width=\"400\" src=\"https://github.com/john-rocky/PersonSegmentationSampler/assets/23278992/7e806f4d-0323-431a-89e8-816163e5c3f5\"\u003e \u003cimg width=\"400\" src=\"https://github.com/john-rocky/PersonSegmentationSampler/assets/23278992/8589f89b-367d-4777-8ebd-6e78253c4b33\"\u003e\n\n| Google Drive Link | Size | Output |Original Project | License |year|\n| ------------- | ------------- | ------------- | ------------- | ------------- |------------- |\n| [DASR](https://drive.google.com/drive/folders/10J2ehHewK2ppS5ToDqmtJ2Ei5k8vcdL0?usp=sharing) | 12.1 MB | Image(RGB 1024x1024)| [The-Learning-And-Vision-Atelier-LAVA/DASR](https://github.com/The-Learning-And-Vision-Atelier-LAVA/DASR)  | [MIT](https://github.com/The-Learning-And-Vision-Atelier-LAVA/DASR/blob/main/LICENSE) |2022|\n\n\n# Low Light Enhancement\n\n### StableLLVE\n\nLearning Temporal Consistency for Low Light Video Enhancement from Single Images.\n\n\u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/148664179-4d0cd417-d8f9-4d0e-bc05-cff3a4a30b5a.jpg\"\u003e \u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/148664220-c756198f-e8c5-4ea8-8737-59c004d2f08c.jpg\"\u003e \n\n| Google Drive Link | Size | Output |Original Project | License |Year|\n| ------------- | ------------- | ------------- | ------------- | ------------- | ------------- |\n| [StableLLVE](https://drive.google.com/file/d/1-9xry7XeCJYsZadxcfTscjGi_Sna5NhM/view?usp=sharing) | 17.3 MB | Image(RGB 512x512)| [zkawfanx/StableLLVE](https://github.com/zkawfanx/StableLLVE)  | [MIT](https://github.com/zkawfanx/StableLLVE/blob/main/LICENSE) |2021|\n\n### Zero-DCE\n\nZero-Reference Deep Curve Estimation for Low-Light Image Enhancement\n\n\u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/151897265-7c3c0295-69c3-4c90-9dcc-d04bbcfd41a3.jpg\"\u003e \u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/151897430-f16d84f0-170c-4e54-a08d-ad4d5b6ca47a.jpg\"\u003e \n\n| Google Drive Link | Size | Output |Original Project | License |Year|Conversion Script|\n| ------------- | ------------- | ------------- | ------------- | ------------- | ------------- | ------------- |\n| [Zero-DCE](https://drive.google.com/file/d/1-0lxlBNFm8E_y9ImhS2wxq0p1ZJlXyoA/view?usp=sharing) | 320KB | Image(RGB 512x512)| [Li-Chongyi/Zero-DCE](https://github.com/Li-Chongyi/Zero-DCE)  | [See Repo](https://github.com/Li-Chongyi/Zero-DCE) |2021|[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1sh3O-4EvYv49Rlm59beH6koHe0sYxc2r?usp=sharing)|\n\n### Retinexformer\n\nRetinexformer: One-stage Retinex-based Transformer for Low-light Image Enhancement\n\n\u003cimg width=\"256\" src=\"https://github.com/john-rocky/PersonSegmentationSampler/assets/23278992/296650ba-e2a9-49ba-b2d6-be02e8b56f09\"\u003e \u003cimg width=\"256\" src=\"https://github.com/john-rocky/PersonSegmentationSampler/assets/23278992/eac9f78a-2b00-442a-b73f-01760268184e\"\u003e \n\n| Google Drive Link | Size | Output |Original Project | License |Year|Conversion Script|\n| ------------- | ------------- | ------------- | ------------- | ------------- | ------------- | ------------- |\n| [ZRetinexformer FiveK](https://drive.google.com/drive/folders/1ea6vBuLG-z4TAK4iU6vrgABAAlHuDdhy?usp=drive_link) | 3.4MB | Image(RGB 512x512)| [caiyuanhao1998/Retinexformer](https://github.com/caiyuanhao1998/Retinexformer)  | [MIT](https://github.com/caiyuanhao1998/Retinexformer?tab=MIT-1-ov-file#readme) |2023|[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/10PtPI4V72Pp6PQZcrah-vClGzjKLaGGK?usp=sharing)|\n| [ZRetinexformer NTIRE](https://drive.google.com/drive/folders/14piyZVwzu4Abpfgwh2HIKoubeeE-3qoq?usp=drive_link) | 3.4MB | Image(RGB 512x512)| [caiyuanhao1998/Retinexformer](https://github.com/caiyuanhao1998/Retinexformer)  | [MIT](https://github.com/caiyuanhao1998/Retinexformer?tab=MIT-1-ov-file#readme) |2023|[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/10PtPI4V72Pp6PQZcrah-vClGzjKLaGGK?usp=sharing)|\n\n# Image Restoration\n\n### MPRNet\n\nMulti-Stage Progressive Image Restoration.\n\nDebluring\n\n\u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/149243725-79c68d8e-db6c-4114-ac64-738cd6b5c37c.jpg\"\u003e \u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/149243509-7eff6ae8-65c2-45ba-bfa2-d730657ab2bd.png\"\u003e \n\nDenoising\n\n\u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/149241165-534c54db-7e98-4356-8613-44acb93d4c6a.png\"\u003e \u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/149242199-7cc3e456-7c8d-441c-b0aa-f1b6ca19a5c9.png\"\u003e \n\nDeraining\n\n\u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/149241095-91791593-416e-41b0-8a95-71819cb7fb06.jpg\"\u003e \u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/149241720-afe94607-e9c2-45bb-988d-3c322d7dde1a.jpg\"\u003e \n\n| Google Drive Link | Size | Output |Original Project | License |Year|\n| ------------- | ------------- | ------------- | ------------- | ------------- | ------------- |\n| [MPRNetDebluring](https://drive.google.com/file/d/1--5L6BxxbyYGY9ey5WCIrl7g1yYBN27U/view?usp=sharing) | 137.1 MB | Image(RGB 512x512)| [swz30/MPRNet](https://github.com/swz30/MPRNet)  | [MIT](https://github.com/swz30/MPRNet/blob/main/LICENSE.md) |2021|\n| [MPRNetDeNoising](https://drive.google.com/file/d/1-04xou-UgoflZb7MqTBycCpuLWKUAj0i/view?usp=sharing) | 108 MB | Image(RGB 512x512)| [swz30/MPRNet](https://github.com/swz30/MPRNet)  | [MIT](https://github.com/swz30/MPRNet/blob/main/LICENSE.md) |2021|\n| [MPRNetDeraining](https://drive.google.com/file/d/1tGvjj49yaDym24vGdGqr1VKOtGd7ALKB/view?usp=sharing) | 24.5 MB | Image(RGB 512x512)| [swz30/MPRNet](https://github.com/swz30/MPRNet)  | [MIT](https://github.com/swz30/MPRNet/blob/main/LICENSE.md) |2021|\n\n\n### MIRNetv2\n\nLearning Enriched Features for Fast Image Restoration and Enhancement.\n\nDenoising\n\n\u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/176293658-6715e545-fe9b-4b21-b374-1394740efdde.png\"\u003e \u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/176293741-dc77831a-86d0-4bdc-a667-96d318d064c4.png\"\u003e \n\nSuper Resolution\n\n\u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/176276244-93535414-bc0e-423d-9c0a-18ba432391a4.jpg\"\u003e \u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/176276266-75228905-2266-4c2c-b42a-026803a0da3b.jpg\"\u003e \n\nContrast Enhancement\n\n\u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/176286891-563c92cd-1817-406a-babb-7dd9b0cccc01.jpg\"\u003e \u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/176296935-bce82abf-6420-43ae-924e-5b98ee956431.jpg\"\u003e \n\nLow Light Enhancement\n\n\u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/176283269-145a5ce4-709a-4eea-91a7-b924b598a03d.jpg\"\u003e \u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/176283354-c45a6247-b1c2-43f8-8b43-8fcf0ddac64f.jpg\"\u003e \n\n| Google Drive Link | Size | Output |Original Project | License |Year|Conversion Script|\n| ------------- | ------------- | ------------- | ------------- | ------------- | ------------- | ------------- |\n| [MIRNetv2Denoising](https://drive.google.com/file/d/1-HY2AhQV84LUZMadsbIi4TGBhEntAOaF/view?usp=sharing) | 42.5 MB | Image(RGB 512x512)| [swz30/MIRNetv2](https://github.com/swz30/MIRNetv2)  | [ACADEMIC PUBLIC LICENSE](https://github.com/swz30/MIRNetv2/blob/main/LICENSE.md) |2022|[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1lSWCn0et08hdS3sgKc40c7VXUvKcqCSi?usp=sharing)|\n| [MIRNetv2SuperResolution](https://drive.google.com/file/d/1-BLfJj8xK_bw-GsGLfRR9uMvuA2VOqsh/view?usp=sharing) | 42.5 MB | Image(RGB 512x512)| [swz30/MIRNetv2](https://github.com/swz30/MIRNetv2)  | [ACADEMIC PUBLIC LICENSE](https://github.com/swz30/MIRNetv2/blob/main/LICENSE.md) |2022|[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1lSWCn0et08hdS3sgKc40c7VXUvKcqCSi?usp=sharing)|\n| [MIRNetv2ContrastEnhancement](https://drive.google.com/file/d/1--q9Decpy1ZZbSifiE26SkpXstoadpM8/view?usp=sharing) | 42.5 MB | Image(RGB 512x512)| [swz30/MIRNetv2](https://github.com/swz30/MIRNetv2)  | [ACADEMIC PUBLIC LICENSE](https://github.com/swz30/MIRNetv2/blob/main/LICENSE.md) |2022|[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1lSWCn0et08hdS3sgKc40c7VXUvKcqCSi?usp=sharing)|\n| [MIRNetv2LowLightEnhancement](https://drive.google.com/file/d/1Yh3FCogRfQ8k7Hh_UIZAnGwwhXHX6k6P/view?usp=sharing) | 42.5 MB | Image(RGB 512x512)| [swz30/MIRNetv2](https://github.com/swz30/MIRNetv2)  | [ACADEMIC PUBLIC LICENSE](https://github.com/swz30/MIRNetv2/blob/main/LICENSE.md) |2022|[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1lSWCn0et08hdS3sgKc40c7VXUvKcqCSi?usp=sharing)|\n\n# Image Generation\n\n### [MobileStyleGAN](https://drive.google.com/drive/folders/1rUV6AXwp8JhPPmkog-0r0AUGzUvN9DmW?usp=sharing)\n\u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/147397892-773c55ca-55fc-422b-a95b-a729eda04077.JPG\"\u003e \u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/147397894-e2d3a1ef-7afa-410a-9580-f09ef7157c50.JPG\"\u003e \n\n| Google Drive Link | Size | Output | Original Project | License | Sample Project |\n| ------------- | ------------- | ------------- | ------------- |  ------------- |  ------------- | \n| [MobileStyleGAN](https://drive.google.com/drive/folders/1rUV6AXwp8JhPPmkog-0r0AUGzUvN9DmW?usp=sharing) | 38.6MB  | Image(Color 1024 × 1024)| [bes-dev/MobileStyleGAN.pytorch](https://github.com/bes-dev/MobileStyleGAN.pytorch)  | [Nvidia Source Code License-NC](https://github.com/bes-dev/MobileStyleGAN.pytorch/blob/develop/LICENSE-NVIDIA) | [CoreML-StyleGAN](https://github.com/john-rocky/CoreML-StyleGAN) |\n\n\n### [DCGAN](https://drive.google.com/file/d/132GrmmuETSLTml1zWyLUnIksclP-8vGw/view?usp=sharing)\n\u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/144690829-3a4cebcf-ee73-4df0-b8db-1dfc2e616798.png\"\u003e\n\n| Google Drive Link | Size | Output | Original Project | \n| ------------- | ------------- | ------------- | ------------- | \n| [DCGAN](https://drive.google.com/file/d/132GrmmuETSLTml1zWyLUnIksclP-8vGw/view?usp=sharing)　| 9.2MB | MultiArray | [TensorFlowCore](https://www.tensorflow.org/tutorials/generative/dcgan)|\n\n\n# Image2Image\n\n### [Anime2Sketch](https://drive.google.com/file/d/1-52NnZ1kajZI5Rk0tn3DegpU38la_jYk/view?usp=sharing)\n\u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/147990751-9ac35e43-b9a6-4db2-af5c-37978322240d.jpeg\"\u003e \u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/147990892-d676142c-62c4-433d-9835-337b1293bfc4.jpeg\"\u003e\n\n| Google Drive Link | Size | Output | Original Project | License | Usage |\n| ------------- | ------------- | ------------- | ------------- | ------------- |  ------------- | \n| [Anime2Sketch](https://drive.google.com/file/d/1-52NnZ1kajZI5Rk0tn3DegpU38la_jYk/view?usp=sharing) | 217.7MB  | Image(Color 512 × 512)| [Mukosame/Anime2Sketch](https://github.com/Mukosame/Anime2Sketch)  | [MIT](https://github.com/Mukosame/Anime2Sketch/blob/master/LICENSE)| Drop an image to preview|\n\n\n### [AnimeGAN2Face_Paint_512_v2](https://drive.google.com/file/d/1phSgcAz3LNbk2v2RoSESmr7PFxTAHcxb/view?usp=sharing)\n\u003cimg width=\"400\" src=\"https://camo.qiitausercontent.com/74a02b6e0b80e52c2ae3af798c93eea9aa3e394d/68747470733a2f2f71696974612d696d6167652d73746f72652e73332e61702d6e6f727468656173742d312e616d617a6f6e6177732e636f6d2f302f3233353235392f30313764616563342d333933312d643664662d303339322d6162313039303237313963642e706e67\"\u003e \u003cimg width=\"400\" src=\"https://camo.qiitausercontent.com/311349da47136ff9ce61701d09ce59dc663c95bf/68747470733a2f2f71696974612d696d6167652d73746f72652e73332e61702d6e6f727468656173742d312e616d617a6f6e6177732e636f6d2f302f3233353235392f66633337653936332d383533302d333731312d643163662d3335366266646666316665322e706e67\"\u003e\n\n| Google Drive Link | Size | Output | Original Project | Conversion Script |\n| ------------- | ------------- | ------------- | ------------- |  ------------- | \n| [AnimeGAN2Face_Paint_512_v2](https://drive.google.com/file/d/1phSgcAz3LNbk2v2RoSESmr7PFxTAHcxb/view?usp=sharing) | 8.6MB  | Image(Color 512 × 512)| [bryandlee/animegan2-pytorch](https://github.com/bryandlee/animegan2-pytorch#additional-model-weights)  |[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1WGAxMaikjNIfqdGRndEOmNyeVf33nGNh?usp=sharing) |\n\n\n### [Photo2Cartoon](https://drive.google.com/file/d/1xFWZ9Rf1o_LtwBpmSw2zSwPGk2FY6Wya/view?usp=sharing)\n\u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/147394190-01a2c6be-5056-4f83-b4af-3f494dad47f4.png\"\u003e \u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/147394192-46de7634-c3ce-481f-afa5-8a7ab4603f2e.png\"\u003e\n\n| Google Drive Link | Size | Output | Original Project | License | Note |\n| ------------- | ------------- | ------------- | ------------- | ------------- | ------------- | \n| [Photo2Cartoon](https://drive.google.com/file/d/1xFWZ9Rf1o_LtwBpmSw2zSwPGk2FY6Wya/view?usp=sharing) | 15.2 MB  | Image(Color 256 × 256)| [minivision-ai/photo2cartoon](https://github.com/minivision-ai/photo2cartoon) | [MIT](https://github.com/minivision-ai/photo2cartoon/blob/master/LICENSE) | The output is little bit different from the original model. It cause some operations were converted replaced　manually. |\n\n### [AnimeGANv2_Hayao](https://drive.google.com/file/d/1G53oZ1hiMcLJs1loN_fe_VmBVfegh9ha/view?usp=sharing)\n\u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/147421574-8f38367c-d5c5-442d-9742-7b2bb24d43e4.jpg\"\u003e \u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/147421569-df8e2e59-fef8-4db4-9cb2-65ee960ef705.png\"\u003e\n\n| Google Drive Link | Size | Output | Original Project | Sample |\n| ------------- | ------------- | ------------- | ------------- | ------------- |\n| [AnimeGANv2_Hayao](https://drive.google.com/file/d/1G53oZ1hiMcLJs1loN_fe_VmBVfegh9ha/view?usp=sharing)　| 8.7MB | Image(256 x 256) | [TachibanaYoshino/AnimeGANv2](https://github.com/TachibanaYoshino/AnimeGANv2)|[AnimeGANv2-iOS](https://github.com/john-rocky/AnimeGANv2-iOS)|\n\n\n### [AnimeGANv2_Paprika](https://drive.google.com/file/d/10drMcmF67iREUK8NY8ekMHrsyVirs5XT/view?usp=sharing)\n\u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/144670978-1447ce28-db49-4cf9-b484-3142ef703ade.jpg\"\u003e \u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/144671455-f7258cc9-1a3e-49df-8bbb-03285c619b17.png\"\u003e\n\n| Google Drive Link | Size | Output | Original Project | \n| ------------- | ------------- | ------------- | ------------- | \n| [AnimeGANv2_Paprika](https://drive.google.com/file/d/10drMcmF67iREUK8NY8ekMHrsyVirs5XT/view?usp=sharing)　| 8.7MB | Image(256 x 256) | [TachibanaYoshino/AnimeGANv2](https://github.com/TachibanaYoshino/AnimeGANv2)|\n\n\n### [WarpGAN Caricature](https://drive.google.com/file/d/1HE3qvfjuXZMFelRcmmGsLzoO5dV8lnaQ/view?usp=sharing)\n\u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/147397894-e2d3a1ef-7afa-410a-9580-f09ef7157c50.JPG\"\u003e \u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/147421276-574edb28-f909-4830-afd0-5cb41328bdba.JPG\"\u003e\n\n| Google Drive Link | Size | Output | Original Project | \n| ------------- | ------------- | ------------- | ------------- | \n| [WarpGAN Caricature](https://drive.google.com/file/d/1HE3qvfjuXZMFelRcmmGsLzoO5dV8lnaQ/view?usp=sharing)　| 35.5MB | Image(256 x 256) | [seasonSH/WarpGAN](https://github.com/seasonSH/WarpGAN)|\n\n### [UGATIT_selfie2anime](https://drive.google.com/file/d/1o15OO0Kn0tq79fFkmBm3PES93IRQOxB-/view?usp=sharing)\n\n\u003cimg width=\"400\" alt=\"スクリーンショット 2021-12-27 8 18 33\" src=\"https://user-images.githubusercontent.com/23278992/147422391-847b3c75-3e6e-419e-9a53-f6138b9ac813.png\"\u003e \u003cimg width=\"400\" alt=\"スクリーンショット 2021-12-27 8 28 11\" src=\"https://user-images.githubusercontent.com/23278992/147422387-2b71a135-cd9c-4f02-8223-65bf365cda4e.png\"\u003e\n\n| Google Drive Link | Size | Output | Original Project | \n| ------------- | ------------- | ------------- | ------------- | \n| [UGATIT_selfie2anime](https://drive.google.com/file/d/1o15OO0Kn0tq79fFkmBm3PES93IRQOxB-/view?usp=sharing) | 266.2MB(quantized) | Image(256x256) | [taki0112/UGATIT](https://github.com/taki0112/UGATIT)  |\n\n### CartoonGAN\n\n| Google Drive Link | Size | Output | Original Project | \n| ------------- | ------------- | ------------- | ------------- | \n| [CartoonGAN_Shinkai](https://drive.google.com/file/d/1j9bvHFBX5yctSeaE8FEvUv-r-hEVvXwi/view?usp=sharing)　| 44.6MB | MultiArray | [mnicnc404/CartoonGan-tensorflow](https://github.com/mnicnc404/CartoonGan-tensorflow)|\n| [CartoonGAN_Hayao](https://drive.google.com/file/d/1-2dTGge4fza-TTBI9actkg_xp91zYT-F/view?usp=sharing)　| 44.6MB | MultiArray | [mnicnc404/CartoonGan-tensorflow](https://github.com/mnicnc404/CartoonGan-tensorflow)|\n| [CartoonGAN_Hosoda](https://drive.google.com/file/d/1-5VB1g7kRt0KMe6u37fi_t18l-Zn_wr1/view?usp=sharing)　| 44.6MB | MultiArray | [mnicnc404/CartoonGan-tensorflow](https://github.com/mnicnc404/CartoonGan-tensorflow)|\n| [CartoonGAN_Paprika](https://drive.google.com/file/d/1-5x3TYugodcnGYiEEDitFqMQPVHsCDs_/view?usp=sharing)　| 44.6MB | MultiArray | [mnicnc404/CartoonGan-tensorflow](https://github.com/mnicnc404/CartoonGan-tensorflow)|\n\n### [Fast-Neural-Style-Transfer](https://drive.google.com/file/d/1o15OO0Kn0tq79fFkmBm3PES93IRQOxB-/view?usp=sharing)\n\n\u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/155708074-ab651a7c-b882-40f1-9ce5-a94e80bac62d.jpg\"\u003e \u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/155708089-ee888836-3f18-41a1-97fd-72e17e604c9a.jpg\"\u003e\n\u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/155707184-403ad161-6354-4ce4-87d4-284e323b1261.jpg\"\u003e \u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/155708401-f76481ad-1de7-4262-acc2-9dcb61c89784.jpg\"\u003e\n\u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/155707199-b77b2583-c355-4406-bc9a-3248492df2c7.jpg\"\u003e \u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/155706861-97e629a0-4322-4924-94ed-cb10c966bfb8.jpg\"\u003e\n\n| Google Drive Link | Size | Output |Original Project | License |Year|\n| ------------- | ------------- | ------------- | ------------- | ------------- | ------------- |\n| [fast-neural-style-transfer-cuphead](https://drive.google.com/file/d/1-LLQF8T6MrcpdiYZkdGZAizkj7c-lJ9e/view?usp=sharing) | 6.4MB | Image(RGB 960x640)| [eriklindernoren/Fast-Neural-Style-Transfer](https://github.com/eriklindernoren/Fast-Neural-Style-Transfer)  | [MIT](https://github.com/eriklindernoren/Fast-Neural-Style-Transfer/blob/master/LICENSE) |2019|\n| [fast-neural-style-transfer-starry-night](https://drive.google.com/file/d/1-HLHIrV_WwZJsEkZ34nTfqnlIHIe04Vy/view?usp=sharing) |  6.4MB | Image(RGB 960x640)| [eriklindernoren/Fast-Neural-Style-Transfer](https://github.com/eriklindernoren/Fast-Neural-Style-Transfer)  | [MIT](https://github.com/eriklindernoren/Fast-Neural-Style-Transfer/blob/master/LICENSE) |2019|\n| [fast-neural-style-transfer-mosaic](https://drive.google.com/file/d/1-GmnewjDz2Cs7-CfXPSFIgOruQvBbK2X/view?usp=sharing) |  6.4MB | Image(RGB 960x640)| [eriklindernoren/Fast-Neural-Style-Transfer](https://github.com/eriklindernoren/Fast-Neural-Style-Transfer)  | [MIT](https://github.com/eriklindernoren/Fast-Neural-Style-Transfer/blob/master/LICENSE) |2019|\n\n### [White_box_Cartoonization](https://drive.google.com/file/d/1QGNJzEp0fo6oOryTos1dazEKaS34WzZC/view?usp=sharing)\n\nLearning to Cartoonize Using White-box Cartoon Representations\n\n\u003cimg width=\"400\" img src=\"https://user-images.githubusercontent.com/23278992/189335273-d05f9cdb-1375-4553-8146-2f598676a95b.jpg\"\u003e \u003cimg width=\"400\" img src=\"https://user-images.githubusercontent.com/23278992/189335456-5184b222-9b55-429e-850a-adf4879a47fc.jpg\"\u003e\n\n| Google Drive Link | Size | Output | Original Project | License |Year|\n| ------------- | ------------- | ------------- | ------------- | ------------- | ------------- | \n| [White_box_Cartoonization](https://drive.google.com/file/d/1QGNJzEp0fo6oOryTos1dazEKaS34WzZC/view?usp=sharing) | 5.9MB | Image(1536x1536) | [SystemErrorWang/White-box-Cartoonization](https://github.com/SystemErrorWang/White-box-Cartoonization)  |[creativecommons](https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode)|CVPR2020|\n\n### [FacialCartoonization](https://drive.google.com/file/d/1CJH4tuR3ArKvxrmAE_44lbsAwUzjtyXi/view?usp=sharing)\n\nWhite-box facial image cartoonizaiton\n\n\u003cimg width=\"400\" img src=\"https://user-images.githubusercontent.com/23278992/189454922-1a95ca25-4031-47a7-8914-9fb8e5c7ff58.png\"\u003e \u003cimg width=\"400\" img src=\"https://user-images.githubusercontent.com/23278992/189454801-19d6ef20-7361-41a5-b85b-5dbd7cf05adb.png\"\u003e\n\n| Google Drive Link | Size | Output | Original Project | License |Year|\n| ------------- | ------------- | ------------- | ------------- | ------------- | ------------- | \n| [FacialCartoonization](https://drive.google.com/file/d/1CJH4tuR3ArKvxrmAE_44lbsAwUzjtyXi/view?usp=sharing) | 8.4MB | Image(256x256) | [SystemErrorWang/FacialCartoonization](https://github.com/SystemErrorWang/FacialCartoonization)  |[creativecommons](https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode)|2020|\n\n# Inpainting\n\n### AOT-GAN-for-Inpainting\n\n\u003cimg width=\"400\" src=\"https://user-images.githubusercontent.com/23278992/220097750-0cd3f94e-1c60-4e03-b9dc-e1ea14f3e57c.gif\"\u003e\n\n| Google Drive Link | Size | Output | Original Project | License | Note | Sample Project |\n| ------------- | ------------- | ------------- | ------------- |------------- |------------- |------------- |\n|[AOT-GAN-for-Inpainting](https://drive.google.com/file/d/16rF46DFcDPherlpgjuL60065xcP2N3nv/view?usp=share_link)|60.8MB| MLMultiArray(3,512,512) |[researchmm/AOT-GAN-for-Inpainting](https://github.com/researchmm/AOT-GAN-for-Inpainting)|[Apache2.0](https://github.com/open-mmlab/mmediting/blob/master/LICENSE)|To use see sample.| [john-rocky/Inpainting-CoreML](https://github.com/john-rocky/Inpainting-CoreML) |\n\n### [Lama](https://drive.google.com/drive/folders/1s_uICJQykFFxgVubpBNeLLDL0JsxgdCd?usp=sharing)\n\n\u003cimg width=\"400\" src=\"https://github.com/john-rocky/PersonSegmentationSampler/assets/23278992/847f874b-7174-4317-8313-f82685bdd20c\"\u003e\n\n| Google Drive Link | Size | Input | Output | Original Project | License | Note | Sample Project | Conversion Script |\n| ------------- | ------------- | ------------- | ------------- |------------- |------------- |------------- |------------- |------------- |\n|[Lama](https://drive.google.com/drive/folders/1s_uICJQykFFxgVubpBNeLLDL0JsxgdCd?usp=sharing)|216.6MB| Image (Color 800 × 800), Image (GrayScale 800 × 800)| Image (Color 800 × 800) |[advimman/lama](https://github.com/advimman/lama)|[Apache2.0](https://github.com/advimman/lama/blob/main/LICENSE)|To use see sample.| [john-rocky/lama-cleaner-iOS](https://github.com/john-rocky/lama-cleaner-iOS) | [mallman/CoreMLaMa](https://github.com/mallman/CoreMLaMa)|\n\n# Monocular Depth Estimation\n\n### [MiDaS](https://drive.google.com/file/d/1agGnt5Cq5CGzoNDl9Nb-3u7pB5SrIbN4/view?usp=share_link)\nTowards Robust Monocular Depth Estimation: Mixing Datasets for Zero-shot Cross-dataset Transfer\n\n\u003cimg width=\"400\" img src=\"https://user-images.githubusercontent.com/23278992/224542700-701472b7-fa8c-4824-a966-f9490f7c780f.jpg\"\u003e \u003cimg width=\"400\" img src=\"https://user-images.githubusercontent.com/23278992/224542703-11ed535f-40c6-4a45-8e3f-d42ce2b9c6f9.jpeg\"\u003e\n\n| Google Drive Link | Size | Output | Original Project | License |Year|Conversion Script |\n| ------------- | ------------- | ------------- | ------------- | ------------- | ------------- | ------------- | \n| [MiDaS_Small](https://drive.google.com/file/d/1agGnt5Cq5CGzoNDl9Nb-3u7pB5SrIbN4/view?usp=share_link) | 66.3MB | MultiArray(1x256x256) | [isl-org/MiDaS](https://github.com/isl-org/MiDaS)  |[MIT](https://github.com/isl-org/MiDaS/blob/master/LICENSE)|2022|[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/13cVDO6gYdQvbKimcfbgGOfuoQmrTbarU?usp=sharing) |\n\n# Stable Diffusion\n\n### [stable-diffusion-v1-5](https://drive.google.com/file/d/1dqYEdhSPi7y0Dgans-Fk7_ViNviUTUJj/view?usp=share_link)\n\n\u003cimg width=\"400\" alt=\"スクリーンショット 2023-03-21 18 52 18\" src=\"https://user-images.githubusercontent.com/23278992/226571395-0815ebdb-39e1-4763-bb16-25c33c5ae9bb.png\"\u003e\n\n| Google Drive Link  | Original Model |Original Project | License | Run on mac |Conversion Script |Year|\n| ------------- | ------------- | ------------- | ------------- | ------------- | ------------- | ------------- | \n| [stable-diffusion-v1-5](https://drive.google.com/file/d/1dqYEdhSPi7y0Dgans-Fk7_ViNviUTUJj/view?usp=share_link) |[runwayml/stable-diffusion-v1-5](https://huggingface.co/runwayml/stable-diffusion-v1-5)|[runwayml/stable-diffusion](https://github.com/runwayml/stable-diffusion)  |[Open RAIL M license](https://huggingface.co/runwayml/stable-diffusion-v1-5)|[godly-devotion/MochiDiffusion](https://github.com/godly-devotion/MochiDiffusion)|[godly-devotion/MochiDiffusion](https://github.com/godly-devotion/MochiDiffusion/wiki/How-to-convert-Stable-Diffusion-models-to-Core-ML#requirements) |2022|\n\n### [pastel-mix](https://drive.google.com/file/d/1cp3VoF1R-as8_lScWGUoxl-BNVX3d7vb/view?usp=share_link)\n\nPastel Mix - a stylized latent diffusion model.This model is intended to produce high-quality, highly detailed anime style with just a few prompts.\n\n\u003cimg width=\"400\" alt=\"スクリーンショット 2023-03-21 19 54 13\" src=\"https://user-images.githubusercontent.com/23278992/226585761-3eaba244-7fea-4529-af36-0962fe624936.png\"\u003e\n\n| Google Drive Link  | Original Model | License | Run on mac |Conversion Script |Year|\n| ------------- | ------------- | ------------- |  ------------- | ------------- | ------------- | \n| [pastelMixStylizedAnime_pastelMixPrunedFP16](https://drive.google.com/file/d/1cp3VoF1R-as8_lScWGUoxl-BNVX3d7vb/view?usp=share_link) |[andite/pastel-mix](https://huggingface.co/andite/pastel-mix)|[Fantasy.ai](https://huggingface.co/andite/pastel-mix)|[godly-devotion/MochiDiffusion](https://github.com/godly-devotion/MochiDiffusion)|[godly-devotion/MochiDiffusion](https://github.com/godly-devotion/MochiDiffusion/wiki/How-to-convert-Stable-Diffusion-models-to-Core-ML#requirements) |2023|\n\n### [Orange Mix](https://drive.google.com/file/d/1ueU-RuZIsl3b3F7uu_gBa_SfAtGTzTI5/view?usp=share_link)\n\n\u003cimg width=\"800\" alt=\"スクリーンショット 2023-03-21 23 34 13\" src=\"https://user-images.githubusercontent.com/23278992/226656177-8260d83c-6e93-4d9b-8fbd-154a0028f88d.png\"\u003e\n\n| Google Drive Link  | Original Model | License | Run on mac |Conversion Script |Year|\n| ------------- | ------------- | ------------- |  ------------- | ------------- | ------------- | \n| [AOM3_orangemixs](https://drive.google.com/file/d/1ueU-RuZIsl3b3F7uu_gBa_SfAtGTzTI5/view?usp=share_link) |[WarriorMama777/OrangeMixs](https://huggingface.co/WarriorMama777/OrangeMixs)|[CreativeML OpenRAIL-M](https://huggingface.co/WarriorMama777/OrangeMixs)|[godly-devotion/MochiDiffusion](https://github.com/godly-devotion/MochiDiffusion)|[godly-devotion/MochiDiffusion](https://github.com/godly-devotion/MochiDiffusion/wiki/How-to-convert-Stable-Diffusion-models-to-Core-ML#requirements) |2023|\n\n### [Counterfeit](https://drive.google.com/file/d/1Kt_8hnGUGnJAUnuergLki37GKnWjWOJp/view?usp=share_link)\n\n\u003cimg width=\"800\" alt=\"スクリーンショット 2023-03-22 0 47 53\" src=\"https://user-images.githubusercontent.com/23278992/226731352-c6ad077d-6f91-4a03-a6e5-dd01ce398d9c.png\"\u003e\n\n| Google Drive Link  | Original Model | License | Run on mac |Conversion Script |Year|\n| ------------- | ------------- | ------------- |  ------------- | ------------- | ------------- | \n| [Counterfeit-V2.5](https://drive.google.com/file/d/1Kt_8hnGUGnJAUnuergLki37GKnWjWOJp/view?usp=share_link) |[gsdf/Counterfeit-V2.5](https://huggingface.co/gsdf/Counterfeit-V2.5)|-|[godly-devotion/MochiDiffusion](https://github.com/godly-devotion/MochiDiffusion)|[godly-devotion/MochiDiffusion](https://github.com/godly-devotion/MochiDiffusion/wiki/How-to-convert-Stable-Diffusion-models-to-Core-ML#requirements) |2023|\n\n\n### [anything-v4](https://drive.google.com/file/d/1yF55CGy4I3BKom_E70lLkU6N03nSvjDt/view?usp=share_link)\n\n\u003cimg width=\"800\" alt=\"スクリーンショット 2023-03-22 0 47 53\" src=\"https://user-images.githubusercontent.com/23278992/226734890-8b48320f-5b4c-4f6c-bd56-07954f573582.png\"\u003e\n\n| Google Drive Link  | Original Model | License | Run on mac |Conversion Script |Year|\n| ------------- | ------------- | ------------- |  ------------- | ------------- | ------------- | \n| [anything-v4.5](https://drive.google.com/file/d/1yF55CGy4I3BKom_E70lLkU6N03nSvjDt/view?usp=share_link) |[andite/anything-v4.0](https://huggingface.co/andite/anything-v4.0)|[Fantasy.ai](https://huggingface.co/andite/anything-v4.0)|[godly-devotion/MochiDiffusion](https://github.com/godly-devotion/MochiDiffusion)|[godly-devotion/MochiDiffusion](https://github.com/godly-devotion/MochiDiffusion/wiki/How-to-convert-Stable-Diffusion-models-to-Core-ML#requirements) |2023|\n\n### [Openjourney](https://drive.google.com/file/d/1KIhSG7pHjgldg7r2mm1Yuwa85BceFLsk/view?usp=share_link)\n\n\u003cimg width=\"800\" alt=\"スクリーンショット 2023-03-22 7 49 39\" src=\"https://user-images.githubusercontent.com/23278992/226909583-42efdb55-e2f0-4331-be0d-7f4bcd2c8b2c.png\"\u003e\n\n| Google Drive Link  | Original Model | License | Run on mac |Conversion Script |Year|\n| ------------- | ------------- | ------------- |  ------------- | ------------- | ------------- | \n| [Openjourney](https://drive.google.com/file/d/1KIhSG7pHjgldg7r2mm1Yuwa85BceFLsk/view?usp=share_link) |[prompthero/openjourney](https://huggingface.co/prompthero/openjourney)|-|[godly-devotion/MochiDiffusion](https://github.com/godly-devotion/MochiDiffusion)|[godly-devotion/MochiDiffusion](https://github.com/godly-devotion/MochiDiffusion/wiki/How-to-convert-Stable-Diffusion-models-to-Core-ML#requirements) |2023|\n\n### [dreamlike-photoreal-2](https://drive.google.com/file/d/1D5RXYE52wyXPq6TdCHM8DIkP4dxHafwt/view?usp=share_link)\n\n\u003cimg width=\"800\" alt=\"dreamlike\" src=\"https://user-images.githubusercontent.com/23278992/226922948-1af2334b-0798-4aef-bfb4-464438dde1b9.png\"\u003e\n\n| Google Drive Link  | Original Model | License | Run on mac |Conversion Script |Year|\n| ------------- | ------------- | ------------- |  ------------- | ------------- | ------------- | \n| [dreamlike-photoreal-2.0](https://drive.google.com/file/d/1D5RXYE52wyXPq6TdCHM8DIkP4dxHafwt/view?usp=share_link) |[dreamlike-art/dreamlike-photoreal-2.0](https://huggingface.co/dreamlike-art/dreamlike-photoreal-2.0)|[CreativeML OpenRAIL-M](https://huggingface.co/dreamlike-art/dreamlike-photoreal-2.0)|[godly-devotion/MochiDiffusion](https://github.com/godly-devotion/MochiDiffusion)|[godly-devotion/MochiDiffusion](https://github.com/godly-devotion/MochiDiffusion/wiki/How-to-convert-Stable-Diffusion-models-to-Core-ML#requirements) |2023|\n\n## Models converted by someone other than me.\n\n### [Stable Diffusion](https://github.com/apple/ml-stable-diffusion)\n[apple/ml-stable-diffusion](https://github.com/apple/ml-stable-diffusion)\n\n## How to use in a xcode project.\n\n### Option 1,implement Vision request.\n\n```swift:\n\nimport Vision\nlazy var coreMLRequest:VNCoreMLRequest = {\n   let model = try! VNCoreMLModel(for: modelname().model)\n   let request = VNCoreMLRequest(model: model, completionHandler: self.coreMLCompletionHandler)\n   return request\n   }()\n\nlet handler = VNImageRequestHandler(ciImage: ciimage,options: [:])\n   DispatchQueue.global(qos: .userInitiated).async {\n   try? handler.perform([coreMLRequest])\n}\n```\n\nIf the model has Image type output:\n\n```swift\nlet result = request?.results?.first as! VNPixelBufferObservation\nlet uiimage = UIImage(ciImage: CIImage(cvPixelBuffer: result.pixelBuffer))\n```\n\nElse the model has Multiarray type output:\n\nFor visualizing multiArray as image, Mr. Hollance’s “CoreML Helpers” are very convenient.\n[CoreML Helpers](https://github.com/hollance/CoreMLHelpers)\n\n[Converting from MultiArray to Image with CoreML Helpers.](https://medium.com/@rockyshikoku/converting-from-multiarray-to-image-with-coreml-helpers-59fdc34d80d8)\n\n```swift:\nfunc coreMLCompletionHandler（request：VNRequest？、error：Error？）{\n   let = coreMLRequest.results？.first as！VNCoreMLFeatureValueObservation\n   let multiArray = result.featureValue.multiArrayValue\n   let cgimage = multiArray？.cgImage（min：-1、max：1、channel：nil）\n```\n\n### Option 2,Use [CoreGANContainer](https://github.com/john-rocky/CoreGANContainer). You can use models with dragging\u0026dropping into the container project. \n\n# Make the model lighter\nYou can make the model size lighter with Quantization if you want.\nhttps://coremltools.readme.io/docs/quantization\n\u003eThe lower the number of bits, more the chances of degrading the model accuracy. The loss in accuracy varies with the model.\n\n```python\nimport coremltools as ct\nfrom coremltools.models.neural_network import quantization_utils\n\n# load full precision model\nmodel_fp32 = ct.models.MLModel('model.mlmodel')\n\nmodel_fp16 = quantization_utils.quantize_weights(model_fp32, nbits=16)\n# nbits can be 16(half size model), 8(1/4), 4(1/8), 2, 1\n```\n\n##### quantized sample (U2Net)\n\n##### InputImage / nbits=32(original) / nbits=16 / nbits=8 / nbits=4\n\n\u003cimg src=\"https://user-images.githubusercontent.com/23278992/147712147-0959c0b9-9d4b-4049-9dd9-7a9d1ffa0eed.JPEG\" width=200\u003e \u003cimg src=\"https://user-images.githubusercontent.com/23278992/147712215-dd0c8788-75ad-4676-804a-fdd47233daa6.JPG\" width=200\u003e \u003cimg src=\"https://user-images.githubusercontent.com/23278992/147712220-d02ab436-9716-4cdc-91d3-8b6f3aa01fac.JPG\" width=200\u003e \u003cimg src=\"https://user-images.githubusercontent.com/23278992/147712259-aabf5ecf-db59-476d-8f36-e6027dfb91e2.JPG\" width=200\u003e \u003cimg src=\"https://user-images.githubusercontent.com/23278992/147712328-a44f538c-aa3e-431d-98ec-626239262e01.JPG\" width=200\u003e\n\n\n\n# Thanks\nCover image was taken from Ghibli free images. \n\nOn YOLOv5 convertion, [dbsystel/yolov5-coreml-tools](https://github.com/dbsystel/yolov5-coreml-tools) give me the super inteligent convert script. \n\nAnd all of original projects\n\n# Auther\n\nDaisuke Majima\nFreelance engineer. iOS/MachineLearning/AR\nI can work on mobile ML projects and AR project.\nFeel free to contact: rockyshikoku@gmail.com\n\n[GitHub](https://github.com/john-rocky)\n[Twitter](https://twitter.com/JackdeS11)\n[Medium](https://rockyshikoku.medium.com/)\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjohn-rocky%2FCoreML-Models","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fjohn-rocky%2FCoreML-Models","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjohn-rocky%2FCoreML-Models/lists"}