Requirements

• tensorflow-gpu>=1.1
• keras==2.0.8
• imgaug
• opencv-python
• h5py
• pyqt==5.6
• pickle
• tqdm

For Training and Validation

Open Yolo.ipynb in jupyter notebook and follow below instruction

• Initialization
  • Download COCO detection data from http://cocodataset.org/#download
    • http://images.cocodataset.org/zips/train2014.zip <= train images
    • http://images.cocodataset.org/zips/val2014.zip <= validation images
    • http://images.cocodataset.org/annotations/annotations_trainval2014.zip <= train and validation annotations
  • Run this script in terminal to convert annotations in COCO format to VOC format
    • python coco2pascal.py
  • Download pre-trained weights from https://drive.google.com/file/d/1yUW7b1gAp0GecJf1NH8KvcXaRL0ZmaFN/view?usp=sharing
  • Specify the directory of train annotations (train_annot_folder) and train images (train_image_folder)
  • Specify the directory of validation annotations (valid_annot_folder) and validation images (valid_image_folder)
  • Specity the path of pre-trained weights by setting variable wt_path
• Load the pretrained weights
• Perform training

For Application

• Download file of trained weights with 9 classes(person, bicycle, car, motorcycle, bus, train, truck, traffic light, stop sign) https://drive.google.com/file/d/1aAqhRy4OnaQgNP8HausSyPZmF-8E57Vj/view?usp=sharing

• run this in terminal for the application python obj2.py

Note:: Some Sample images and videos included for testing in images folder

For any issues email at [email protected]