https://github.com/naufalahnaf17/pytorch-cv-project

several computer vision projects in learning to create deep learning models, especially in the field of computer vision, starting from classification, object detection and others
https://github.com/naufalahnaf17/pytorch-cv-project

beginner-project computer-vision fine-tuning huggingface onnxruntime python pytorch

Last synced: 6 months ago
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several computer vision projects in learning to create deep learning models, especially in the field of computer vision, starting from classification, object detection and others

• Host: GitHub
• URL: https://github.com/naufalahnaf17/pytorch-cv-project
• Owner: naufalahnaf17
• Created: 2024-09-12T07:14:41.000Z (almost 2 years ago)
• Default Branch: main
• Last Pushed: 2024-09-25T17:38:13.000Z (almost 2 years ago)
• Last Synced: 2024-10-06T02:06:00.674Z (almost 2 years ago)
• Topics: beginner-project, computer-vision, fine-tuning, huggingface, onnxruntime, python, pytorch
• Language: Python
• Homepage:
• Size: 1.91 MB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# Computer Vision Project

These are some mini projects I created using Pytorch for computer vision tasks

in this repo I will create a mini project with various tasks in computer vision such as image classification, object detection, object segmentation, GAN and many more

add a star to get updates from this repo

#### Repo Update

- **26 Sep 2024 -> inference next js plant-species-classification**

- **25 Sep 2024 -> inference next js cat-and-dogs-classification**

- **20 Sep 2024 -> facemask-detection**

- **17 Sep 2024 -> manga-text-detection**

- **17 Sep 2024 -> plant-species-classification**

- **16 Sep 2024 -> cat-and-dogs-classification**

### Dont have CUDA for Training ? Download Model Here

| Model Name         | Model URL                                                                |

| ----------------- | ------------------------------------------------------------------ |

| Cat and Dogs | [click here to download](https://drive.google.com/file/d/1Tfh30c0BShuSTTpvgeCYBHK2aZdkhjV0/view?usp=drive_link) |

| Plant Species | [click here to download](https://drive.google.com/file/d/1OYLj2TIK2oTglLJMRt2t7BW2tGLM6178/view?usp=drive_link) |

| Manga Text | [click here to download](https://drive.google.com/file/d/1kI_RXo2hoQ9fQWU3CcB1wrw3-CFOfKe4/view?usp=drive_link) |

| Facemask Detection | [click here to download](https://drive.google.com/file/d/1J2AKUaLGDlDAXvZCgUNtsz-Hhyqw7EVv/view?usp=drive_link) |

## cat-and-dogs-classification (Created : 16-09-2024)

in this project, I focused on fine-tune the resnet-50 model then exported it to onnx format.

which initially resnet-50 outputs approximately 1000 classes into just 2 classes according to the dataset that has been downloaded, namely cats and dogs

- Loss : 0.06402150790199812

- Accuracy : 98.46762234305487%

- Epochs : 5

![Pred_3](cat-and-dogs-classification/screenshot/save_3.PNG)

## plant-species-classification (Created : 17-09-2024)

in this project, I focused on fine-tune the google/vit-base-patch16-224 model then exported it to onnx format.

which initially google/vit-base-patch16-224 outputs approximately 1000 classes into just 47 classes according to the dataset that has been downloaded, namely house-plant-species

- Loss : 0.305279920695395

- Accuracy : 93.55418434246046%

- Epochs : 5

![Pred_1](plant-species-classification/screenshot/save_1.JPG)

## manga-text-detection (Created : 17-09-2024)

in this project, I focused on fine-tune the faster-RCNN model then exported it to onnx format.

create object detection on text in manga pages with the manga-text-detection dataset

- Loss : 0.105800

- Epochs : 25

- MAP : 0.9

- MAP-50 : 1.0

- MAP-75 : 0.9901

![Pred_1](manga-text-detection/screenshot/save_1.JPG)

![Pred_2](manga-text-detection/screenshot/save_2.JPG)

## facemask-detection (Created : 20-09-2024)

in this project, I focused on fine-tune the YOLOv10 model then exported it to onnx format.

create object detection on facemask-dataset

- Loss : 0.405800

- Epochs : 50

- MAP : 0.908

- MAP-50 : 0.934

- MAP-75 : 0.666

![Pred_1](facemask-detection/screenshot/save_1.JPG)

![Pred_2](facemask-detection/screenshot/save_2.JPG)

## Todo List 

- [x] Fine tune resnet-50 on the cats and dogs dataset

  - [x] Create inference with opencv and onnxruntime (python)

  - [x] Create inference with next.js and onnxruntime-web

  - [ ] Create Inference with kotlin

- [x] Fine tune vit-base-224 on the plant species dataset

  - [x] Create inference with opencv and onnxruntime (python)

  - [x] Create inference with next.js and onnxruntime-web

  - [ ] Create Inference with kotlin

- [x] Fine tune Faster-RCNN on the manga text detection dataset

  - [x] Create inference with opencv and onnxruntime (python)

  - [ ] Create inference with next.js and onnxruntime-web

- [x] Fine tune YOLO-V10 on the facemask dataset

  - [x] Create inference with opencv and onnxruntime (python)

  - [ ] Create inference with next.js and onnxruntime-web

  - [ ] Create Inference with kotlin and run with input uint8

## Authors

- [@naufalahnaf17](https://www.github.com/naufalahnaf17)