{"id":18136126,"url":"https://github.com/cupidonsauce173/blur-detection","last_synced_at":"2026-05-17T00:04:16.513Z","repository":{"id":138177045,"uuid":"377649040","full_name":"CupidonSauce173/Blur-Detection","owner":"CupidonSauce173","description":"This is a very simple python program detecting the amount of blur and seperating images into different folders and creating a Excel sheet doc with all the necessary values.","archived":false,"fork":false,"pushed_at":"2021-06-17T02:26:52.000Z","size":31,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-04-06T16:50:24.054Z","etag":null,"topics":["blur","detection","images","opencv","python"],"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/CupidonSauce173.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":"2021-06-16T23:05:15.000Z","updated_at":"2021-09-06T05:28:54.000Z","dependencies_parsed_at":null,"dependency_job_id":"aeb31ab3-1047-499a-9ef4-84e8042b1a5c","html_url":"https://github.com/CupidonSauce173/Blur-Detection","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/CupidonSauce173/Blur-Detection","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/CupidonSauce173%2FBlur-Detection","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/CupidonSauce173%2FBlur-Detection/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/CupidonSauce173%2FBlur-Detection/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/CupidonSauce173%2FBlur-Detection/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/CupidonSauce173","download_url":"https://codeload.github.com/CupidonSauce173/Blur-Detection/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/CupidonSauce173%2FBlur-Detection/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":265427438,"owners_count":23763318,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","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":["blur","detection","images","opencv","python"],"created_at":"2024-11-01T14:10:55.284Z","updated_at":"2025-10-24T18:03:14.560Z","avatar_url":"https://github.com/CupidonSauce173.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Python-Image-Blur-Detection\n\n## Installation\n\n### Getting the script from github\nInstall manually: \n1. Clone the repository and unpack it via winrar or any zip manager and copy the files into a directory for the script.\nInstall via git:\n1. git clone https://github.com/CupidonSauce173/Blur-Detection.git\n\n### Installing the dependencies\nThis script require few modules, tqdm, imutils and cv2. Use the package manager PIP : https://pip.pypa.io/en/stable/ to install all dependencies.\n1. Install tqdm\n```bash\npip install tqdm\n```\n2. Install imutils\n```bash\npip install imutils\n```\n3. Install cv2\n```bash\npip install opencv-python\n```\n\n## How to run\nFirst, create an \"images\" folder next to the script if you wish to use default values.\nSecond, put all the images you want in the 'images' folder or any other folder you wish. Then, run \n```bash\npython detect_blur.py --images images\n```\n## Usage\nThere are few arguments you can put to customize your experience.\n```\n--images \u003cdirectory_path\u003e, leave it to 'images' if you put all your images in the provided images folder, or else, use something like --images \"path/to/folder\".\n--threshold \u003cint value\u003e, leave it for a default value of 100 (100%). This let you set the maximum amount of blur an image can have before being flagged as blurry.\n--output_file_name \u003cfile name\u003e, leave it for a default value of \"results.txt\". This let you customize the output file of the script at the end of the process.\n\n--images =\u003e --i\n--threshold =\u003e --t\n--output_file_name =\u003e --o\n\nexamples of commands\npython detect_blur.py --i E:\\turcot_images --t 20 --o \"image_result.txt\"\n```\n\n## Notes\nThere will be a progress bar to show you how many images you process per second and also to show you where the script is.\n\n## Little explaination of why I did this\nThis project helped the project Turcot with analysing which pictures were blurry from the drone they used to do the cartography of the whole sector. In my system, it can process around 2.1 pictures / second (pictures of 5472x3648 pixels and of around 4.5mb - 6.5mb).\n\n\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcupidonsauce173%2Fblur-detection","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fcupidonsauce173%2Fblur-detection","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcupidonsauce173%2Fblur-detection/lists"}