It is a graphical image annotation tool. Designed a python based auto labeling tool ,where in we can load a tensorflow model and images folder.Model runs inference on images and draws bounding box and class label.

1. Clone this repository.
2. Go to the directory where label.py exists.
3. Download Faster R-CNN, Mask R-CNN, ssdlite_mobilenet_v2 models from this drive link.Unzip files and copy them in the directory.

• Label_Image
  • faster_rcnn
  • Mask_RCNN
  • ssdlite_mobilenet_v2
  • label.py
  • label.txt
  • detection.py ( detailed code to get detected labels and co ordinates from model )

4. Run the python file.

python label.py

5. Then there appears UI. Select images folder by clicking 'Directory' and then once loaded click 'Select Image' to select desired image.
6. Select model and Detection threshold as required.
7. Also select object that you want the model to detect.
8. Click 'Detect' and Save annotations of detected objects.

• This tool confines to the models Faster R-CNN, Mask R-CNN, ssdlite_mobilenet_v2.

• Download tensorflow models from here.
• List model names in model_list array in label.py.
• Make sure you create a label.txt where in object names of your Dataset are listed.

• tensorflow
• PyQt5
• Opencv

• Tensorflow model zoo
• LabelImg Tool