{"id":22615577,"url":"https://github.com/sovit-123/deep-learning-image-super-resolution","last_synced_at":"2026-04-29T18:34:06.376Z","repository":{"id":111786169,"uuid":"273411205","full_name":"sovit-123/Deep-Learning-Image-Super-Resolution","owner":"sovit-123","description":"This is a deep learning project based on the Image Super-Resolution Using Deep Convolutional Networks - SRCNN paper using the PyTorch deep learning library.","archived":false,"fork":false,"pushed_at":"2020-06-24T13:42:14.000Z","size":24650,"stargazers_count":3,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-03-29T00:42:30.044Z","etag":null,"topics":["computer","convolutional-neural-networks","deep-learning","image-processing","image-super-resolution","neural-network","python","pytorch","pytorch-implementation"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/sovit-123.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2020-06-19T05:25:54.000Z","updated_at":"2024-12-17T06:16:50.000Z","dependencies_parsed_at":null,"dependency_job_id":"33f97d4d-2bd3-495f-93cf-ce7fec8a39d3","html_url":"https://github.com/sovit-123/Deep-Learning-Image-Super-Resolution","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/sovit-123/Deep-Learning-Image-Super-Resolution","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sovit-123%2FDeep-Learning-Image-Super-Resolution","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sovit-123%2FDeep-Learning-Image-Super-Resolution/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sovit-123%2FDeep-Learning-Image-Super-Resolution/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sovit-123%2FDeep-Learning-Image-Super-Resolution/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/sovit-123","download_url":"https://codeload.github.com/sovit-123/Deep-Learning-Image-Super-Resolution/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sovit-123%2FDeep-Learning-Image-Super-Resolution/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":32439220,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-04-29T18:12:22.909Z","status":"ssl_error","status_checked_at":"2026-04-29T18:11:33.322Z","response_time":110,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.5:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["computer","convolutional-neural-networks","deep-learning","image-processing","image-super-resolution","neural-network","python","pytorch","pytorch-implementation"],"created_at":"2024-12-08T19:08:24.424Z","updated_at":"2026-04-29T18:34:06.361Z","avatar_url":"https://github.com/sovit-123.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Deep Learning Image Super Resolution\n\n\n\n## \u003cu\u003eWhat is the Project About\u003c/u\u003e\n\n* This is a deep learning project based on the [Image Super-Resolution Using Deep Convolutional Networks - SRCNN](http://mmlab.ie.cuhk.edu.hk/projects/SRCNN.html) paper using the **PyTorch** deep learning library.\n\n\n\n## \u003cu\u003eFramework and Dependencies\u003c/u\u003e\n\n* **The project is built on PyTorch 1.4.** \n* You will need MATLAB to execute the `.m` files.\n\n\n\n## \u003cu\u003eDirectory Structure\u003c/u\u003e\n\n* The following is the directory structure to arrange everything for the project.\n\n  ```\n  ├───input\n  │   ├───bicubic_2x\n  │   ├───bicubic_4x\n  │   ├───bicubic_rgb_2x\n  │   ├───bicubic_rgb_4x\n  │   ├───General100\n  │   ├───Set14\n  │   ├───Set5\n  │   ├───T91\n  │   ├───T91_G100\n  |    train_mscale.h5\n  ├───outputs\n  └───src\n  ```\n\n* `input`: contains the datasets that are used for training and testing. The `train_mscale.h5` is the training datasets that gets generated after running the `generate_train.m` file. \n\n  * Currently the model has been trained on both `T91` and `General100` image datasets. Both of these datasets are merged into `T91_G100` folder. The same corresponds to in the `generate_train.m` file.\n  * The `bicubic_x` folders contain the blurred images that we use for testing. Generate those images using the `bicubic.py` file inside the `src` folder.\n\n* The `outputs` folder will contain all the output files along with the trained model.\n\n* `src` contains the python and MATLAB files.\n\n***Note***: *I have take the MATLAB codes from the [SRCNN-Keras](https://github.com/YapengTian/SRCNN-Keras) repository. The original `generate_train.m` file generate greyscale sub-images. I have formatted the code so as to generate colored (RGB) sub-images. As such, in this project, you will be able to train a neural network model that can carry out super-resolution on RGB images.*  *Please go through the code for more details*.\n\n\n\n## \u003cu\u003eDataset\u003c/u\u003e\n\n* You will find the datasets used in this project and more super-resolution datasets [here](https://github.com/xinntao/BasicSR/wiki/Prepare-datasets-in-LMDB-format).\n\n\n\n## \u003cu\u003eExecution\u003c/u\u003e\n\n* `generate_train.m`: To generate the `train_mscale.h5` sub-images.\n* Execute the python scripts while being within the `src` folder in the terminal.\n  * `python bicubic.py --path ../input/Set14 --scale-factor 2x`: To create low-resolution bicubic images for the Set14 data by a scaling factor of 2x.\n  * `python train.py`: For training the SRCNN model.\n  * `python test.py --input ../input/bicubic_rgb_2x`: To generate high resolution images of the 2x scaled low-resolution images.\n\n\n\n## \u003cu\u003eSome Results\u003c/u\u003e\n\n* The following are from testing on the 2x scaled low-resolution images.\n\n![](https://github.com/sovit-123/Deep-Learning-Image-Super-Resolution/blob/master/input/bicubic_rgb_2x/baboon.png?raw=true)\n\n![](https://github.com/sovit-123/Deep-Learning-Image-Super-Resolution/blob/master/outputs/outputs_baboon.png?raw=true)\n\n![](https://github.com/sovit-123/Deep-Learning-Image-Super-Resolution/blob/master/input/bicubic_rgb_2x/comic.png?raw=true)\n\n![](https://github.com/sovit-123/Deep-Learning-Image-Super-Resolution/blob/master/outputs/outputs_comic.png?raw=true)\n\n![](https://github.com/sovit-123/Deep-Learning-Image-Super-Resolution/blob/master/input/bicubic_rgb_2x/zebra.png?raw=true)\n\n![](https://github.com/sovit-123/Deep-Learning-Image-Super-Resolution/blob/master/outputs/outputs_zebra.png?raw=true)\n\n\n\n\n\n## \u003cu\u003eReferences\u003c/u\u003e\n\n* [Image Super-Resolution Using Deep Convolutional Networks - SRCNN](http://mmlab.ie.cuhk.edu.hk/projects/SRCNN.html).\n\n* [ SRCNN-Keras](https://github.com/YapengTian/SRCNN-Keras): For the `generate_train.m` file to create the `train_mscale.h5` training data.\n* [SRCNN-Tensorflow](https://github.com/jinsuyoo/SRCNN-Tensorflow): For the test images.\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsovit-123%2Fdeep-learning-image-super-resolution","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsovit-123%2Fdeep-learning-image-super-resolution","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsovit-123%2Fdeep-learning-image-super-resolution/lists"}