Comments (1)
This is only tested for tensorflow 2.3 and Keras 2.4. Try installing that. Tbh all of this is pretty dated now and you may be better off finding a more recent repo.
This repo let's you train a custom image detector using the state-of-the-art YOLOv3 computer vision algorithm. For a short write up check out this medium post. This repo works with TensorFlow 2.3 and Keras 2.4.
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Related Issues (20)
- Print accuracy and val_accuracy
- Unable to run Download_and_Convert_YOLO_weights HOT 1
- Confidence score and class label not needed to print HOT 2
- Ran into "Building wheel for opencv-python (PEP 517)" build error during requirements.txt install
- Numpy version error and weights not downlaoding HOT 3
- Python 3.10.x Support HOT 6
- Printing model summary HOT 1
- self._traceback = tf_stack.extract_stack()
- validation set and loss in tensorboard graph HOT 4
- Models,anchors,classes loading time - for optimization HOT 1
- Multiple Labels in an image HOT 2
- IoU threshold for non Max suppression HOT 1
- Error when training tiny YOLO on early stopping HOT 5
- Own trained model does not detect any objects
- Detect.py stuck after import
- issue in Detector.py
- Yolov3_tiny_Inference Error
- Error (cannot import name 'multi_gpu_model' from 'tensorflow.keras.utils') when running Detector.py
- customizing yolo
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