{"id":25478342,"url":"https://github.com/konynour/tf-object-detection","last_synced_at":"2026-05-01T08:32:06.906Z","repository":{"id":278126320,"uuid":"934589357","full_name":"konynour/TF-Object-Detection","owner":"konynour","description":"This project implements an object detection system using TensorFlow and OpenCV, designed to identify and classify objects in images or video streams. By utilizing pre-trained models from the TensorFlow Object Detection API, this project allows users to detect multiple objects in real-time or from static images.","archived":false,"fork":false,"pushed_at":"2025-02-18T06:12:15.000Z","size":67970,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-02-18T06:28:53.623Z","etag":null,"topics":["frozen","jupyter-notebook","matplotlip","opencv","python-script","python3","tensorflow","tensorflow-object-detection-api"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","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/konynour.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":"2025-02-18T04:44:18.000Z","updated_at":"2025-02-18T06:12:18.000Z","dependencies_parsed_at":"2025-02-18T06:39:29.912Z","dependency_job_id":null,"html_url":"https://github.com/konynour/TF-Object-Detection","commit_stats":null,"previous_names":["konynour/tf-object-detection"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/konynour%2FTF-Object-Detection","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/konynour%2FTF-Object-Detection/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/konynour%2FTF-Object-Detection/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/konynour%2FTF-Object-Detection/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/konynour","download_url":"https://codeload.github.com/konynour/TF-Object-Detection/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":239488757,"owners_count":19647261,"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":["frozen","jupyter-notebook","matplotlip","opencv","python-script","python3","tensorflow","tensorflow-object-detection-api"],"created_at":"2025-02-18T14:31:29.244Z","updated_at":"2025-11-06T09:30:29.570Z","avatar_url":"https://github.com/konynour.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Object Detection using TensorFlow and OpenCV\n\n## 📌 Overview\n\nThis project implements object detection using a pre-trained **SSD MobileNet v2** model from the TensorFlow Model Zoo. The model is loaded using OpenCV's Deep Neural Network (DNN) module, and it performs real-time object detection on images.\n\n## ⚠️ Disclaimer\n\n**This project is intended for educational purposes only. The author is not responsible for any misuse.**\n\n## 🚀 Features\n\n- Loads and processes images for object detection.\n- Uses a pre-trained **SSD MobileNet v2** model.\n- Detects multiple objects in an image and labels them with bounding boxes.\n- Configurable detection threshold.\n\n## 📂 Requirements\n\n- Python 3.x\n- OpenCV (`cv2`)\n- Matplotlib\n- numpy\n- os\n- urllib\n- zipfile\n- TensorFlow Model Zoo (pre-trained models)\n\n## 🔧 Installation\n\n1. Clone this repository:\n   ```sh\n   git remote add origin https://github.com/konynour/TF-Object-Detection.git   ```\n2. Navigate to the project folder:\n   ```sh\n   cd ObjectDetection\n   ```\n3. Install dependencies:\n   ```sh\n   pip install opencv-python numpy matplotlib\n   ```\n\n## ⚙️ Usage\n\n### 1️⃣ Load and Configure the Model\n\n- Download and extract the **SSD MobileNet v2** model from TensorFlow Model Zoo.\n- Place the `frozen_inference_graph.pb` and its configuration file `.pbtxt` inside the `models/` directory.\n\n### 2️⃣ Run Object Detection on an Image\n\n```python\nimport cv2\nimport os\nfrom detect import detect_objects, display_objects\n\n# Load an image\nim = cv2.imread(os.path.join(\"images\", \"street.jpg\"))\n\n# Detect objects\nobjects = detect_objects(net, im)\n\n# Display results\ndisplay_objects(im, objects)\n```\n\n### 3️⃣ Adjust Detection Threshold\n\nIf you want to adjust the confidence threshold, you can modify the detection function call:\n\n```python\nim = cv2.imread(os.path.join(\"images\", \"baseball.jpg\"))\nobjects = detect_objects(net, im)\ndisplay_objects(im, objects, threshold=0.2)\n```\n\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkonynour%2Ftf-object-detection","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fkonynour%2Ftf-object-detection","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkonynour%2Ftf-object-detection/lists"}