This project uses the TACO (Trash Annotations in Context) dataset and a pre-trained Tensorflow model to detect trash from images with Python.
This project is really meant as a demonstration. I do not actually recommend using it. It is completely up to you Prerequisites:
- Matplotlib
- Numpy
- Pandas
- OpenCV (for live detection)
- Tensorflow Object Detection
Run the taco.py file and provide an image as "input.png", and the result will be in the "output.png" file. Example:
python .\taco.py
Building label map from examples
Label map witten to labelmap.pbtxt
Reconstructing Tensorflow model
Success!
Using single image detection. Processing...
Finished. Image saved to file
Elapsed: 5.49 seconds
You may also use the 'live' detection mode by setting the USE_LIVE_DETECTION variable to True. This will open up a webcam with OpenCV. Press space to capture an image and wait for a few seconds.
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