{"id":24989810,"url":"https://github.com/clementsan/object_detection_gradio","last_synced_at":"2025-03-29T12:15:25.770Z","repository":{"id":263683992,"uuid":"891137821","full_name":"clementsan/object_detection_gradio","owner":"clementsan","description":"Object detection with Gradio user interface","archived":false,"fork":false,"pushed_at":"2025-01-06T23:00:15.000Z","size":208,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-02-04T13:03:31.661Z","etag":null,"topics":["ai","computer-vision","deep-learning","gradio","object-detection"],"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/clementsan.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":"2024-11-19T19:46:42.000Z","updated_at":"2025-01-06T23:00:18.000Z","dependencies_parsed_at":"2024-11-19T22:38:02.684Z","dependency_job_id":null,"html_url":"https://github.com/clementsan/object_detection_gradio","commit_stats":null,"previous_names":["clementsan/object_detection_gradio"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/clementsan%2Fobject_detection_gradio","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/clementsan%2Fobject_detection_gradio/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/clementsan%2Fobject_detection_gradio/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/clementsan%2Fobject_detection_gradio/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/clementsan","download_url":"https://codeload.github.com/clementsan/object_detection_gradio/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":246180923,"owners_count":20736460,"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":["ai","computer-vision","deep-learning","gradio","object-detection"],"created_at":"2025-02-04T13:03:34.754Z","updated_at":"2025-03-29T12:15:25.746Z","avatar_url":"https://github.com/clementsan.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"---\ntitle: Object Detection\nemoji: 🖼\ncolorFrom: green\ncolorTo: purple\nsdk: gradio\nsdk_version: 5.5.0\napp_file: app.py\npinned: false\nshort_description: Object detection via Gradio\n---\n\n# Object detection\n\nAim: AI-driven object detection (on COCO image dataset)\n\nMachine learning models:\n - facebook/detr-resnet-50, \n - facebook/detr-resnet-101, \n - hustvl/yolos-tiny, \n - hustvl/yolos-small\n\n### \u003cb\u003eTable of contents:\u003c/b\u003e\n - [Execution via command line](#1-execution-via-command-line)\n - [Execution via User Interface ](#2-execution-via-user-interface)\n - [Execution via Gradio client API](#3-execution-via-gradio-client-api)\n - [Deployment on Hugging Face](#4-deployment-on-hugging-face)\n - [Deployment on Docker Hub](#5-deployment-on-docker-hub)\n\n\n## 1. Execution via command line\n\n### 1.1. Use of torch library\n\u003e python detect_torch.py \n\n### 1.2. Use of transformers library\n\u003e python detect_transformers.py\n\n### 1.3. Use of HuggingFace pipeline library\n\u003e python detect_pipeline.py\n\n## 2. Execution via User Interface \nUse of Gradio library for web interface\n\nCommand line:\n\u003e python app.py\n\n\u003cb\u003eNote:\u003c/b\u003e The Gradio app should now be accessible at http://localhost:7860\n\n## 3. Execution via Gradio client API\n\n\u003cb\u003eNote:\u003c/b\u003e Use of existing Gradio server (running locally, in a Docker container, or in the cloud as a HuggingFace space or AWS)\n\n### 3.1. Creation of docker container\n\nCommand lines:\n\u003e sudo docker build -t gradio-app .\n\n\u003e sudo docker run -p 7860:7860 gradio-app\n\nThe Gradio app should now be accessible at http://localhost:7860\n\n### 3.2. Direct inference via API\nCommand line:\n\u003e python inference_API.py\n\n\n## 4. Deployment on Hugging Face\n\nThis web application is available on Hugging Face, via a Gradio space\n\nURL: https://huggingface.co/spaces/cvachet/object_detection_gradio\n\n\n## 5. Deployment on Docker Hub\n\nThis web application is available as a container on Docker Hub\n\nURL: https://hub.docker.com/r/cvachet/object-detection-gradio\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fclementsan%2Fobject_detection_gradio","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fclementsan%2Fobject_detection_gradio","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fclementsan%2Fobject_detection_gradio/lists"}