david8862
commented
5 years ago Yes. It's inherited from the code base of @qqwweee so generally your pretrained model should be compatible. The error you meet is because when generating the darknet backbone it will try to automatically load the pretrained weights from weights/ first. You can go through the QuickStart part to download the weights file to fix it. Or locally change logic to avoid the auto pre-load.
I had previously trained a YOLO model on a custom dataset using this repo : https://github.com/qqwweee/keras-yolo3 This repo is quite similar to this one and the inference mode is exactly the same, as far as image mode is concerned. I give the following command in terminal python yolo.py --model_type=darknet --model_path=./weights/yoloFace.h5 --anchors_path=configs/yolo_anchors.txt --classes_path=configs/face_classes.txt --model_image_size=416x416 --image` This gives me this error :
`Call initializer instance with the dtype argument instead of passing it to the constructor Traceback (most recent call last): File "yolo.py", line 75, in _generate_model yolo_model, _ = get_yolo3_model(self.model_type, num_feature_layers, num_anchors, num_classes, input_shape=self.model_image_size + (3,)) File "/home/dk-tanmay/Desktop/keras-YOLOv3-model-set/yolo3/model.py", line 101, in get_yolo3_model model_body = model_function(input_tensor, num_anchors//3, num_classes, weights_path=weights_path) File "/home/dk-tanmay/Desktop/keras-YOLOv3-model-set/yolo3/models/yolo3_darknet.py", line 60, in yolo_body darknet.load_weights(weights_path, by_name=True) File "/home/dk-tanmay/.virtualenvs/cv/lib/python3.6/site-packages/tensorflow/python/keras/engine/training.py", line 162, in load_weights return super(Model, self).load_weights(filepath, by_name) File "/home/dk-tanmay/.virtualenvs/cv/lib/python3.6/site-packages/tensorflow/python/keras/engine/network.py", line 1412, in load_weights with h5py.File(filepath, 'r') as f: File "/home/dk-tanmay/.virtualenvs/cv/lib/python3.6/site-packages/h5py/_hl/files.py", line 408, in __init__ swmr=swmr) File "/home/dk-tanmay/.virtualenvs/cv/lib/python3.6/site-packages/h5py/_hl/files.py", line 173, in make_fid fid = h5f.open(name, flags, fapl=fapl) File "h5py/_objects.pyx", line 54, in h5py._objects.with_phil.wrapper File "h5py/_objects.pyx", line 55, in h5py._objects.with_phil.wrapper File "h5py/h5f.pyx", line 88, in h5py.h5f.open OSError: Unable to open file (unable to open file: name = 'weights/darknet53.h5', errno = 2, error message = 'No such file or directory', flags = 0, o_flags = 0) During handling of the above exception, another exception occurred: Traceback (most recent call last): File "yolo.py", line 379, in <module> yolo = YOLO_np(**vars(args)) File "yolo.py", line 59, in __init__ self.yolo_model = self._generate_model() File "yolo.py", line 79, in _generate_model assert yolo_model.layers[-1].output_shape[-1] == \ UnboundLocalError: local variable 'yolo_model' referenced before assignmentThe code is going to the darknet53.h5 weights even though I specified the paths for my own weights. The anchors file is the same as full YOLOv3 and I have replaced the classes file. How to resolve this ?
tanmay-bhatnagar
I had previously trained a YOLO model on a custom dataset using this repo : https://github.com/qqwweee/keras-yolo3 This repo is quite similar to this one and the inference mode is exactly the same, as far as image mode is concerned. I give the following command in terminal python yolo.py --model_type=darknet --model_path=./weights/yoloFace.h5 --anchors_path=configs/yolo_anchors.txt --classes_path=configs/face_classes.txt --model_image_size=416x416 --image` This gives me this error :
The code is going to the darknet53.h5 weights even though I specified the paths for my own weights. The anchors file is the same as full YOLOv3 and I have replaced the classes file. How to resolve this ?