PS C:\Projekte\yolo-v3-master> python detect.py images 0.5 0.6 samples_source/2person.jpg
2020-12-18 17:41:08.938946: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'cudart64_110.dll'; dlerror: cudart64_110.dll not found
2020-12-18 17:41:08.945683: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
2020-12-18 17:41:18.865479: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
2020-12-18 17:41:18.984190: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library nvcuda.dll
2020-12-18 17:41:19.908280: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: Quadro M1000M computeCapability: 5.0
coreClock: 1.0715GHz coreCount: 4 deviceMemorySize: 2.00GiB deviceMemoryBandwidth: 74.65GiB/s
2020-12-18 17:41:19.919637: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'cudart64_110.dll'; dlerror: cudart64_110.dll not found
2020-12-18 17:41:19.924839: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'cublas64_11.dll'; dlerror: cublas64_11.dll not found
2020-12-18 17:41:19.935016: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'cublasLt64_11.dll'; dlerror: cublasLt64_11.dll not found
2020-12-18 17:41:19.942377: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'cufft64_10.dll'; dlerror: cufft64_10.dll not found
2020-12-18 17:41:19.958042: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'curand64_10.dll'; dlerror: curand64_10.dll not found
2020-12-18 17:41:19.973101: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'cusolver64_10.dll'; dlerror: cusolver64_10.dll not found
2020-12-18 17:41:19.982206: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'cusparse64_11.dll'; dlerror: cusparse64_11.dll not found
2020-12-18 17:41:19.997208: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'cudnn64_8.dll'; dlerror: cudnn64_8.dll not found
2020-12-18 17:41:20.002890: W tensorflow/core/common_runtime/gpu/gpu_device.cc:1757] Cannot dlopen some GPU libraries. Please make sure the missing libraries mentioned above are installed properly if you would like to use GPU. Follow the guide at https://www.tensorflow.org/install/gpu for how to download and setup the required libraries for your platform.
Skipping registering GPU devices...
2020-12-18 17:41:20.033368: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2020-12-18 17:41:20.046217: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
2020-12-18 17:41:20.056307: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267]
2020-12-18 17:41:20.069136: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
2020-12-18 17:41:20.160534: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:196] None of the MLIR optimization passes are enabled (registered 0 passes)
Traceback (most recent call last):
  File "C:\SDKs etc\Python 3.8\lib\site-packages\tensorflow\python\client\session.py", line 1375, in _do_call
    return fn(*args)
  File "C:\SDKs etc\Python 3.8\lib\site-packages\tensorflow\python\client\session.py", line 1359, in _run_fn
    return self._call_tf_sessionrun(options, feed_dict, fetch_list,
  File "C:\SDKs etc\Python 3.8\lib\site-packages\tensorflow\python\client\session.py", line 1451, in _call_tf_sessionrun
    return tf_session.TF_SessionRun_wrapper(self._session, options, feed_dict,
tensorflow.python.framework.errors_impl.UnimplementedError: The Conv2D op currently only supports the NHWC tensor format on the CPU. The op was given the format: NCHW
         [[{{node yolo_v3_model/conv2d/Conv2D}}]]

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "detect.py", line 146, in <module>
    main(sys.argv[1], float(sys.argv[2]), float(sys.argv[3]), sys.argv[4:])
  File "detect.py", line 47, in main
    detection_result = sess.run(detections, feed_dict={inputs: batch})
  File "C:\SDKs etc\Python 3.8\lib\site-packages\tensorflow\python\client\session.py", line 967, in run
    result = self._run(None, fetches, feed_dict, options_ptr,
  File "C:\SDKs etc\Python 3.8\lib\site-packages\tensorflow\python\client\session.py", line 1190, in _run
    results = self._do_run(handle, final_targets, final_fetches,
  File "C:\SDKs etc\Python 3.8\lib\site-packages\tensorflow\python\client\session.py", line 1368, in _do_run
    return self._do_call(_run_fn, feeds, fetches, targets, options,
  File "C:\SDKs etc\Python 3.8\lib\site-packages\tensorflow\python\client\session.py", line 1394, in _do_call
    raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.UnimplementedError: The Conv2D op currently only supports the NHWC tensor format on the CPU. The op was given the format: NCHW
         [[node yolo_v3_model/conv2d/Conv2D (defined at C:\Projekte\yolo-v3-master\yolo_v3.py:52) ]]

Errors may have originated from an input operation.
Input Source operations connected to node yolo_v3_model/conv2d/Conv2D:
 yolo_v3_model/truediv (defined at C:\Projekte\yolo-v3-master\yolo_v3.py:360)

Original stack trace for 'yolo_v3_model/conv2d/Conv2D':
  File "detect.py", line 146, in <module>
    main(sys.argv[1], float(sys.argv[2]), float(sys.argv[3]), sys.argv[4:])
  File "detect.py", line 42, in main
    detections = model(inputs, training=False)
  File "C:\Projekte\yolo-v3-master\yolo_v3.py", line 362, in __call__
    route1, route2, inputs = darknet53(inputs, training=training,
  File "C:\Projekte\yolo-v3-master\yolo_v3.py", line 82, in darknet53
    inputs = conv2d_fixed_padding(inputs, filters=32, kernel_size=3,
  File "C:\Projekte\yolo-v3-master\yolo_v3.py", line 52, in conv2d_fixed_padding
    return tf.keras.layers.Conv2D(
  File "C:\SDKs etc\Python 3.8\lib\site-packages\tensorflow\python\keras\engine\base_layer_v1.py", line 786, in __call__
    outputs = call_fn(cast_inputs, *args, **kwargs)
  File "C:\SDKs etc\Python 3.8\lib\site-packages\tensorflow\python\keras\layers\convolutional.py", line 248, in call
    outputs = self._convolution_op(inputs, self.kernel)
  File "C:\SDKs etc\Python 3.8\lib\site-packages\tensorflow\python\util\dispatch.py", line 201, in wrapper
    return target(*args, **kwargs)
  File "C:\SDKs etc\Python 3.8\lib\site-packages\tensorflow\python\ops\nn_ops.py", line 1013, in convolution_v2
    return convolution_internal(
  File "C:\SDKs etc\Python 3.8\lib\site-packages\tensorflow\python\ops\nn_ops.py", line 1143, in convolution_internal
    return op(
  File "C:\SDKs etc\Python 3.8\lib\site-packages\tensorflow\python\ops\nn_ops.py", line 2597, in _conv2d_expanded_batch
    return gen_nn_ops.conv2d(
  File "C:\SDKs etc\Python 3.8\lib\site-packages\tensorflow\python\ops\gen_nn_ops.py", line 968, in conv2d
    _, _, _op, _outputs = _op_def_library._apply_op_helper(
  File "C:\SDKs etc\Python 3.8\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 748, in _apply_op_helper
    op = g._create_op_internal(op_type_name, inputs, dtypes=None,
  File "C:\SDKs etc\Python 3.8\lib\site-packages\tensorflow\python\framework\ops.py", line 3528, in _create_op_internal
    ret = Operation(
  File "C:\SDKs etc\Python 3.8\lib\site-packages\tensorflow\python\framework\ops.py", line 1990, in __init__
    self._traceback = tf_stack.extract_stack()