self._traceback = tf_stack.extract_stack()
joaoalves10 opened this issue · 0 comments
joaoalves10 commented
Hi @AntonMu i am having an issue with your repository for a while whenener i try to adpat the detector to my project.
My project aims to detect cars via aerial images taken by an UAV. The detection needs to be real-time.
So, i start by following all your steps to create my own dataset and to train it. I was able to do it all with sucess, which means that right now i have your repository with my dataset and the detector is working fine with the weights that i train and the images that i selected to test.
After this i tried to adapt your Detector.py script to a simpler one that just received an image and detect it, as shown below:
_from PIL import Image
import cv2
from keras_yolo3.yolo import YOLO
def simple():
yolo = YOLO(
**{
"model_path": '/home/joao/catkin_ws/src/offboard_tutorials/src/offboard_control_pkg/lei_controlo_scripts/Data/Model_Weights/trained_weights_final.h5',
"anchors_path": '/home/joao/catkin_ws/src/offboard_tutorials/src/offboard_control_pkg/lei_controlo_scripts/simulacao_completa/keras_yolo3/model_data/yolo_anchors.txt',
"classes_path": '/home/joao/catkin_ws/src/offboard_tutorials/src/offboard_control_pkg/lei_controlo_scripts/Data/Model_Weights/data_classes.txt',
"score": 0.25,
"gpu_num": 1,
"model_image_size": (416, 416),
}
)
fn = "/home/joao/catkin_ws/src/offboard_tutorials/src/offboard_control_pkg/lei_controlo_scripts/Data/Source_Images/Test_Images/1642513427.jpg"
image_matrix = cv2.imread(fn)
fileimage = Image.fromarray(image_matrix)
print('\n\n\n\n start detection \n\n\n\n\n')
out_pred, det_image = yolo.detect_image(fileimage, show_stats=False)
print('\n\n\n\n finished first run\n\n\n\n\n')
print(out_pred)
if __name__ == '__main__':
# main()
simple()_
However, when i try to run it it gives me the following error:
Traceback (most recent call last):
File "/home/joao/env/lib/python3.6/site-packages/tensorflow_core/python/client/session.py", line 1365, in _do_call
return fn(*args)
File "/home/joao/env/lib/python3.6/site-packages/tensorflow_core/python/client/session.py", line 1350, in _run_fn
target_list, run_metadata)
File "/home/joao/env/lib/python3.6/site-packages/tensorflow_core/python/client/session.py", line 1443, in _call_tf_sessionrun
run_metadata)
tensorflow.python.framework.errors_impl.UnimplementedError: The Conv2D op currently does not support grouped convolutions on the CPU. A grouped convolution was attempted to be run because the input depth of 1024 does not match the filter input depth of 1
[[{{node conv2d_58/Conv2D}}]]
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/home/joao/catkin_ws/src/offboard_tutorials/src/offboard_control_pkg/lei_controlo_scripts/simulacao_completa/image_car_detector_com_video.py", line 150, in <module>
simple()
File "/home/joao/catkin_ws/src/offboard_tutorials/src/offboard_control_pkg/lei_controlo_scripts/simulacao_completa/image_car_detector_com_video.py", line 144, in simple
out_pred, det_image = yolo.detect_image(fileimage, show_stats=False)
File "/home/joao/catkin_ws/src/offboard_tutorials/src/offboard_control_pkg/lei_controlo_scripts/simulacao_completa/keras_yolo3/yolo.py", line 162, in detect_image
K.learning_phase(): 0,
File "/home/joao/env/lib/python3.6/site-packages/tensorflow_core/python/client/session.py", line 956, in run
run_metadata_ptr)
File "/home/joao/env/lib/python3.6/site-packages/tensorflow_core/python/client/session.py", line 1180, in _run
feed_dict_tensor, options, run_metadata)
File "/home/joao/env/lib/python3.6/site-packages/tensorflow_core/python/client/session.py", line 1359, in _do_run
run_metadata)
File "/home/joao/env/lib/python3.6/site-packages/tensorflow_core/python/client/session.py", line 1384, in _do_call
raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.UnimplementedError: The Conv2D op currently does not support grouped convolutions on the CPU. A grouped convolution was attempted to be run because the input depth of 1024 does not match the filter input depth of 1
[[node conv2d_58/Conv2D (defined at /env/lib/python3.6/site-packages/tensorflow_core/python/framework/ops.py:1748) ]]
Original stack trace for 'conv2d_58/Conv2D':
File "/catkin_ws/src/offboard_tutorials/src/offboard_control_pkg/lei_controlo_scripts/simulacao_completa/image_car_detector_com_video.py", line 150, in <module>
simple()
File "/catkin_ws/src/offboard_tutorials/src/offboard_control_pkg/lei_controlo_scripts/simulacao_completa/image_car_detector_com_video.py", line 136, in simple
"model_image_size": (416, 416),
File "/catkin_ws/src/offboard_tutorials/src/offboard_control_pkg/lei_controlo_scripts/simulacao_completa/keras_yolo3/yolo.py", line 49, in __init__
self.boxes, self.scores, self.classes = self.generate()
File "/catkin_ws/src/offboard_tutorials/src/offboard_control_pkg/lei_controlo_scripts/simulacao_completa/keras_yolo3/yolo.py", line 83, in generate
Input(shape=(None, None, 3)), num_anchors // 3, num_classes
File "/catkin_ws/src/offboard_tutorials/src/offboard_control_pkg/lei_controlo_scripts/simulacao_completa/keras_yolo3/yolo3/model.py", line 90, in yolo_body
x, y1 = make_last_layers(darknet.output, 512, num_anchors * (num_classes + 5))
File "/catkin_ws/src/offboard_tutorials/src/offboard_control_pkg/lei_controlo_scripts/simulacao_completa/keras_yolo3/yolo3/model.py", line 83, in make_last_layers
)(x)
File "/catkin_ws/src/offboard_tutorials/src/offboard_control_pkg/lei_controlo_scripts/simulacao_completa/keras_yolo3/yolo3/utils.py", line 21, in <lambda>
return reduce(lambda f, g: lambda *a, **kw: g(f(*a, **kw)), funcs)
File "/env/lib/python3.6/site-packages/tensorflow_core/python/keras/engine/base_layer.py", line 854, in __call__
outputs = call_fn(cast_inputs, *args, **kwargs)
File "/env/lib/python3.6/site-packages/tensorflow_core/python/keras/layers/convolutional.py", line 197, in call
outputs = self._convolution_op(inputs, self.kernel)
File "/env/lib/python3.6/site-packages/tensorflow_core/python/ops/nn_ops.py", line 1134, in __call__
return self.conv_op(inp, filter)
File "/env/lib/python3.6/site-packages/tensorflow_core/python/ops/nn_ops.py", line 639, in __call__
return self.call(inp, filter)
File "/env/lib/python3.6/site-packages/tensorflow_core/python/ops/nn_ops.py", line 238, in __call__
name=self.name)
File "/env/lib/python3.6/site-packages/tensorflow_core/python/ops/nn_ops.py", line 2010, in conv2d
name=name)
File "/env/lib/python3.6/site-packages/tensorflow_core/python/ops/gen_nn_ops.py", line 1071, in conv2d
data_format=data_format, dilations=dilations, name=name)
File "/env/lib/python3.6/site-packages/tensorflow_core/python/framework/op_def_library.py", line 794, in _apply_op_helper
op_def=op_def)
File "/env/lib/python3.6/site-packages/tensorflow_core/python/util/deprecation.py", line 507, in new_func
return func(*args, **kwargs)
File "/env/lib/python3.6/site-packages/tensorflow_core/python/framework/ops.py", line 3357, in create_op
attrs, op_def, compute_device)
File "/env/lib/python3.6/site-packages/tensorflow_core/python/framework/ops.py", line 3426, in _create_op_internal
op_def=op_def)
File "/env/lib/python3.6/site-packages/tensorflow_core/python/framework/ops.py", line 1748, in __init__
self._traceback = tf_stack.extract_stack()
I put this script in the same folder as the Detector.py, and i am using the weights that i trained and were working with your repository.
Can you help me?
Thank you