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https://github.com/amirzenoozi/yolo-tf2-object-detection

Object Detection on Image and Video Based on YOLO Model

https://github.com/amirzenoozi/yolo-tf2-object-detection

Science Score: 13.0%

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Keywords

cli coco coco-dataset deep-learning live livestream machine-learning object-detection object-recognition object-segmentation python stream telegram telegram-bot tensorflow tensorflow2 tf2 watchdog yolo yolov3
Last synced: 5 months ago · JSON representation

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Object Detection on Image and Video Based on YOLO Model

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  • Host: GitHub
  • Owner: amirzenoozi
  • Language: Python
  • Default Branch: main
  • Homepage:
  • Size: 28.3 KB
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cli coco coco-dataset deep-learning live livestream machine-learning object-detection object-recognition object-segmentation python stream telegram telegram-bot tensorflow tensorflow2 tf2 watchdog yolo yolov3
Created over 3 years ago · Last pushed over 3 years ago
Metadata Files
Readme

README.md

YOLO Object Detection 🏷️

We Use Pretrained YOLO Model to Detect Objects

Requierments 📦

bash pip install -r requirements.txt

Donwload and Convert pre-trained YOLO-v3 ⏬

```bash

YOLO V3

  • wget https://pjreddie.com/media/files/yolov3.weights -O models/yolov3.weights
  • python converttocheckpoints.py --weights ./models/yolov3.weights --output ./checkpoints/yolov3.tf

YOLO-Tiny V3

  • wget https://pjreddie.com/media/files/yolov3-tiny.weights -O models/yolov3-tiny.weights
  • python convert.py --weights ./models/yolov3-tiny.weights --output ./checkpoints/yolov3-tiny.tf --tiny True ```

Video Frame Extractor CLI Options 🎞️

bash --frame Frame Threshold #default: 1800 (Every Minutes) --src Video File PATH #default: 'sample.mp4'

You Need to Use This Command:

bash python frame.py --frame FRAME_TH --src VIDEO_FILE

Live Stream Frame Extractor CLI Options 📺

bash --frame Frame Threshold #default: 1800 (Every Minutes) --src Video File PATH #default: '' --dir Save Frames Folder Name #default: '' | (Auto-Generate UUID4)

You Need to Use This Command:

bash python live.py --frame FRAME_TH --src STREAM_LINK --dir FOLDER_NAME

if You want to proccess frames during extraction task, you just need to run:

bash python watcher.py --src FOLDER_NAME

Object Detection 📋

bash --weights Path To .tf File #default: 'model/model.h5' --classes Path To Classes File #default: './models/coco.names' --tiny Use Tiny Model Or Not? #default: False --num_classes Number Of Classes In The Model #default: 80 --size Resize Images To #default: 416 --image Path To Input Image #default: './data/sample.jpg' --save Save Or Not #default: False

Then You Just Need To Run This:

```bash

Image

python main.py --image PATHTOIMAGE

Video

python video.py --dir PATHTOFRAMES_DIR ```

Features ✨

  • [x] Detect Default COCO Classes
  • [x] CLI
  • [x] Image Files
  • [x] Video Files
  • [x] Live Stream
  • [ ] Support I18N Classes
  • [ ] Telegram Bot
  • [ ] Rest API
    • [ ] Image Support
    • [ ] Video Support
    • [ ] GIF Support

Owner

  • Name: Amirhossein Douzandeh Zenoozi
  • Login: amirzenoozi
  • Kind: user
  • Location: Bolzano, Italy

🐍 Python Lover‌ 🧠 AI Student 💻 Front-End Engineer

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