thatbrguy / pedestrian-detection Goto Github PK
View Code? Open in Web Editor NEWPedestrian detection using the TensorFlow Object Detection API. Includes multi GPU parallel processing inference.
Pedestrian detection using the TensorFlow Object Detection API. Includes multi GPU parallel processing inference.
Traceback (most recent call last):
File "C:\ProgramData\Anaconda3\envs\tensorflow\lib\multiprocessing\process.py", line 258, in _bootstrap
self.run()
File "C:\ProgramData\Anaconda3\envs\tensorflow\lib\multiprocessing\process.py", line 93, in run
self._target(*self._args, **self._kwargs)
File "E:\Pedestrian-Detector-master\object_detection\inference.py", line 55, in feed
TEST_IMAGE_PATHS, RESULT_IMAGE_PATHS, _ = load_details(args)
NameError: name 'args' is not defined
this is my code:
python object_detection/inference.py
--input_dir=test_images
--output_dir=test_result
--label_map=annotations/label_map.pbtxt
--frozen_graph=object_detection/pedestrian_pb/frozen_inference_graph.pb
--num_output_classes=1
--n_jobs=1
--delay=0
i do not knwo how to fix it , could you help me
Hello,
When I extracted the bounding boxes of a crowded scene, I found that the array associated to the bounding boxes has got a limit of 100 rows. Does it mean that if an image has more than 100 pedestrians the detector won't put them all in bounding boxes ?
How about training ? Can we train a model with a dataset of images that contains more than 100 pedestrians ?
Thank you in advance for your clarifications !
I run the train.py by python3 , and meet the below error. I try transfer the string into bytes, but it no work. so have anyone have any advice.
Traceback (most recent call last):
File "object_detection/train.py", line 53, in
from builders import model_builder
File "/wangpdm/Pedestrian-Detection/object_detection/builders/model_builder.py", line 17, in
from builders import anchor_generator_builder
File "/wangpdm/Pedestrian-Detection/object_detection/builders/anchor_generator_builder.py", line 20, in
from protos import anchor_generator_pb2
File "/wangpdm/Pedestrian-Detection/object_detection/protos/anchor_generator_pb2.py", line 16, in
from protos import grid_anchor_generator_pb2 as object__detection_dot_protos_dot_grid__anchor__generator__pb2
File "/wangpdm/Pedestrian-Detection/object_detection/protos/grid_anchor_generator_pb2.py", line 22, in
serialized_pb=_b('\n3object_detection/protos/grid_anchor_generator.proto\x12\x17 protos"\xcd\x01\n\x13GridAnchorGenerator\x12\x13\n\x06height\x18\x01 \x01(\x05:\x03\x32\x35\x36\x12\x12\n\x05width\x18\x02 \x01(\x05:\x03\x32\x35\x36\x12\x19\n\rheight_stride\x18\x03 \x01(\x05:\x02\x31\x36\x12\x18\n\x0cwidth_stride\x18\x04 \x01(\x05:\x02\x31\x36\x12\x18\n\rheight_offset\x18\x05 \x01(\x05:\x01\x30\x12\x17\n\x0cwidth_offset\x18\x06 \x01(\x05:\x01\x30\x12\x0e\n\x06scales\x18\x07 \x03(\x02\x12\x15\n\raspect_ratios\x18\x08 \x03(\x02')
File "/usr/local/lib/python3.6/dist-packages/google/protobuf/descriptor.py", line 879, in new
return _message.default_pool.AddSerializedFile(serialized_pb)
TypeError: Couldn't parse file content!
Hi,
When I run python create_tf_record.py --data_dir=pwd
--output_dir=pwd
command, I found error:
File "create_tf_record.py", line 180, in <module> tf.app.run() File "/home/administrator/.local/lib/python2.7/site-packages/tensorflow/python/platform/app.py", line 125, in run _sys.exit(main(argv)) File "create_tf_record.py", line 175, in main image_dir, train_examples) File "create_tf_record.py", line 147, in create_tf_record tf_example = dict_to_tf_example(data, label_map_dict, image_dir) File "create_tf_record.py", line 60, in dict_to_tf_example img_path = os.path.join(image_subdirectory, data['filename']) TypeError: string indices must be integers, not str
Hello,
Following your advices, I am going to train a model on Colab.
However, I am currently facing a small problem, I don't know how to pass arguments to my .ipynb.
Can you tell me how you did it ?
By the way, do I need to convert all the .py files called by the train script to .ipynb or is it enough to have only the main file with .ipynb extension (train.py, in this case) ?
Thank you for your help !
Hi, This is awesome!
Can you please help to figure it out how I have to use this code to detect pedestrians on any videos? I am very new to Python!
Thank you so much!
Kasra,
Hello, I found a performance issue in the definition of testResizeToRangePreservesStaticSpatialShape
, object_detection/core/preprocessor_test.py, tf.shape(out_image) will created repeatedly during program execution, resulting in reduced efficiency. I think in_image
, out_image
and out_image_shape
should be created before the loop in testResizeToRangeWithDynamicSpatialShape
.
Looking forward to your reply. Btw, I am very glad to create a PR to fix it if you are too busy.
Hello, I try to train the faster_rcnn_inception_resnet_v2_atrous_coco_2018_01_28 model by launching the train.py script on it, but I get the following ResourceExhaustedError. Do you have any idea on how to solve it ? I tried to change many parameters in pipeline.config, but It doesn't change anything
2018-10-10 14:54:05.313837: I tensorflow/core/common_runtime/bfc_allocator.cc:678] Sum Total of in-use chunks: 1.25GiB
2018-10-10 14:54:05.313845: I tensorflow/core/common_runtime/bfc_allocator.cc:680] Stats:
Limit: 1363345408
InUse: 1338755072
MaxInUse: 1350130944
NumAllocs: 3937
MaxAllocSize: 2561310722018-10-10 14:54:05.313921: W tensorflow/core/common_runtime/bfc_allocator.cc:279] ****************************************************************************************************
2018-10-10 14:54:05.313944: W tensorflow/core/framework/op_kernel.cc:1275] OP_REQUIRES failed at transpose_op.cc:199 : Resource exhausted: OOM when allocating tensor with shape[4,160,42,64] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
INFO:tensorflow:Error reported to Coordinator: OOM when allocating tensor with shape[4,160,42,64] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
[[Node: FirstStageFeatureExtractor/InceptionResnetV2/InceptionResnetV2/Repeat_1/block17_2/Branch_1/Conv2d_0c_7x1/Conv2D-0-TransposeNHWCToNCHW-LayoutOptimizer = Transpose[T=DT_FLOAT, Tperm=DT_INT32, _device="/job:localhost/replica:0/task:0/device:GPU:0"](FirstStageFeatureExtractor/InceptionResnetV2/InceptionResnetV2/Repeat_1/block17_2/Branch_1/Conv2d_0c_7x1/SpaceToBatchND, PermConstNHWCToNCHW-LayoutOptimizer)]]
Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.[[Node: BatchMultiClassNonMaxSuppression/map/while/MultiClassNonMaxSuppression/strided_slice/_1871 = _Recvclient_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device_incarnation=1, tensor_name="edge_11146...ided_slice", tensor_type=DT_INT32, _device="/job:localhost/replica:0/task:0/device:CPU:0"]]
Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.
Traceback (most recent call last):
File "/home/mounir/anaconda3/envs/tflow-gpu/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1278, in _do_call
return fn(*args)
File "/home/mounir/anaconda3/envs/tflow-gpu/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1263, in _run_fn
options, feed_dict, fetch_list, target_list, run_metadata)
File "/home/mounir/anaconda3/envs/tflow-gpu/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1350, in _call_tf_sessionrun
run_metadata)
tensorflow.python.framework.errors_impl.ResourceExhaustedError: OOM when allocating tensor with shape[4,160,42,64] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
[[Node: FirstStageFeatureExtractor/InceptionResnetV2/InceptionResnetV2/Repeat_1/block17_2/Branch_1/Conv2d_0c_7x1/Conv2D-0-TransposeNHWCToNCHW-LayoutOptimizer = Transpose[T=DT_FLOAT, Tperm=DT_INT32, _device="/job:localhost/replica:0/task:0/device:GPU:0"](FirstStageFeatureExtractor/InceptionResnetV2/InceptionResnetV2/Repeat_1/block17_2/Branch_1/Conv2d_0c_7x1/SpaceToBatchND, PermConstNHWCToNCHW-LayoutOptimizer)]]
Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.[[Node: BatchMultiClassNonMaxSuppression/map/while/MultiClassNonMaxSuppression/strided_slice/_1871 = _Recvclient_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device_incarnation=1, tensor_name="edge_11146...ided_slice", tensor_type=DT_INT32, _device="/job:localhost/replica:0/task:0/device:CPU:0"]]
Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/home/mounir/anaconda3/envs/tflow-gpu/lib/python3.6/site-packages/tensorflow/python/training/coordinator.py", line 297, in stop_on_exception
yield
File "/home/mounir/anaconda3/envs/tflow-gpu/lib/python3.6/site-packages/tensorflow/python/training/coordinator.py", line 495, in run
self.run_loop()
File "/home/mounir/anaconda3/envs/tflow-gpu/lib/python3.6/site-packages/tensorflow/python/training/supervisor.py", line 1035, in run_loop
self._sv.global_step])
File "/home/mounir/anaconda3/envs/tflow-gpu/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 877, in run
run_metadata_ptr)
File "/home/mounir/anaconda3/envs/tflow-gpu/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1100, in _run
feed_dict_tensor, options, run_metadata)
File "/home/mounir/anaconda3/envs/tflow-gpu/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1272, in _do_run
run_metadata)
File "/home/mounir/anaconda3/envs/tflow-gpu/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1291, in _do_call
raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.ResourceExhaustedError: OOM when allocating tensor with shape[4,160,42,64] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
[[Node: FirstStageFeatureExtractor/InceptionResnetV2/InceptionResnetV2/Repeat_1/block17_2/Branch_1/Conv2d_0c_7x1/Conv2D-0-TransposeNHWCToNCHW-LayoutOptimizer = Transpose[T=DT_FLOAT, Tperm=DT_INT32, _device="/job:localhost/replica:0/task:0/device:GPU:0"](FirstStageFeatureExtractor/InceptionResnetV2/InceptionResnetV2/Repeat_1/block17_2/Branch_1/Conv2d_0c_7x1/SpaceToBatchND, PermConstNHWCToNCHW-LayoutOptimizer)]]
Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.[[Node: BatchMultiClassNonMaxSuppression/map/while/MultiClassNonMaxSuppression/strided_slice/_1871 = _Recvclient_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device_incarnation=1, tensor_name="edge_11146...ided_slice", tensor_type=DT_INT32, _device="/job:localhost/replica:0/task:0/device:CPU:0"]]
Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.Traceback (most recent call last):
File "/home/mounir/anaconda3/envs/tflow-gpu/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1278, in _do_call
return fn(*args)
File "/home/mounir/anaconda3/envs/tflow-gpu/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1263, in _run_fn
options, feed_dict, fetch_list, target_list, run_metadata)
File "/home/mounir/anaconda3/envs/tflow-gpu/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1350, in _call_tf_sessionrun
run_metadata)
tensorflow.python.framework.errors_impl.ResourceExhaustedError: OOM when allocating tensor with shape[1,384,72,128] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
[[Node: FirstStageFeatureExtractor/InceptionResnetV2/InceptionResnetV2/Mixed_6a/Branch_1/Conv2d_1a_3x3/Conv2D = Conv2D[T=DT_FLOAT, data_format="NCHW", dilations=[1, 1, 1, 1], padding="SAME", strides=[1, 1, 1, 1], use_cudnn_on_gpu=true, _device="/job:localhost/replica:0/task:0/device:GPU:0"](FirstStageFeatureExtractor/InceptionResnetV2/InceptionResnetV2/Mixed_6a/Branch_1/Conv2d_0b_3x3/Relu, FirstStageFeatureExtractor/InceptionResnetV2/Mixed_6a/Branch_1/Conv2d_1a_3x3/weights/read/_3137)]]
Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.[[Node: gradients/SecondStageFeatureExtractor/InceptionResnetV2/Repeat/block8_9/Conv2d_1x1/Conv2D_grad/tuple/control_dependency_1/_5073 = _Recvclient_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device_incarnation=1, tensor_name="edge_13509...pendency_1", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:CPU:0"]]
Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/home/mounir/anaconda3/envs/tflow-gpu/lib/python3.6/site-packages/tensorflow/python/training/supervisor.py", line 995, in managed_session
yield sess
File "/home/mounir/anaconda3/envs/tflow-gpu/lib/python3.6/site-packages/tensorflow/contrib/slim/python/slim/learning.py", line 770, in train
sess, train_op, global_step, train_step_kwargs)
File "/home/mounir/anaconda3/envs/tflow-gpu/lib/python3.6/site-packages/tensorflow/contrib/slim/python/slim/learning.py", line 487, in train_step
run_metadata=run_metadata)
File "/home/mounir/anaconda3/envs/tflow-gpu/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 877, in run
run_metadata_ptr)
File "/home/mounir/anaconda3/envs/tflow-gpu/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1100, in _run
feed_dict_tensor, options, run_metadata)
File "/home/mounir/anaconda3/envs/tflow-gpu/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1272, in _do_run
run_metadata)
File "/home/mounir/anaconda3/envs/tflow-gpu/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1291, in _do_call
raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.ResourceExhaustedError: OOM when allocating tensor with shape[1,384,72,128] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
[[Node: FirstStageFeatureExtractor/InceptionResnetV2/InceptionResnetV2/Mixed_6a/Branch_1/Conv2d_1a_3x3/Conv2D = Conv2D[T=DT_FLOAT, data_format="NCHW", dilations=[1, 1, 1, 1], padding="SAME", strides=[1, 1, 1, 1], use_cudnn_on_gpu=true, _device="/job:localhost/replica:0/task:0/device:GPU:0"](FirstStageFeatureExtractor/InceptionResnetV2/InceptionResnetV2/Mixed_6a/Branch_1/Conv2d_0b_3x3/Relu, FirstStageFeatureExtractor/InceptionResnetV2/Mixed_6a/Branch_1/Conv2d_1a_3x3/weights/read/_3137)]]
Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.[[Node: gradients/SecondStageFeatureExtractor/InceptionResnetV2/Repeat/block8_9/Conv2d_1x1/Conv2D_grad/tuple/control_dependency_1/_5073 = _Recvclient_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device_incarnation=1, tensor_name="edge_13509...pendency_1", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:CPU:0"]]
Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.Caused by op 'FirstStageFeatureExtractor/InceptionResnetV2/InceptionResnetV2/Mixed_6a/Branch_1/Conv2d_1a_3x3/Conv2D', defined at:
File "/home/mounir/PycharmProjects/Pedestrian-Detection-master/object_detection/train.py", line 163, in
tf.app.run()
File "/home/mounir/anaconda3/envs/tflow-gpu/lib/python3.6/site-packages/tensorflow/python/platform/app.py", line 125, in run
_sys.exit(main(argv))
File "/home/mounir/PycharmProjects/Pedestrian-Detection-master/object_detection/train.py", line 159, in main
worker_job_name, is_chief, FLAGS.train_dir)
File "/home/mounir/PycharmProjects/Pedestrian-Detection-master/object_detection/trainer.py", line 228, in train
clones = model_deploy.create_clones(deploy_config, model_fn, [input_queue])
File "/home/mounir/PycharmProjects/Pedestrian-Detection-master/object_detection/deployment/model_deploy.py", line 193, in create_clones
outputs = model_fn(*args, **kwargs)
File "/home/mounir/PycharmProjects/Pedestrian-Detection-master/object_detection/trainer.py", line 165, in _create_losses
prediction_dict = detection_model.predict(images)
File "/home/mounir/PycharmProjects/Pedestrian-Detection-master/object_detection/meta_architectures/faster_rcnn_meta_arch.py", line 531, in predict
image_shape) = self._extract_rpn_feature_maps(preprocessed_inputs)
File "/home/mounir/PycharmProjects/Pedestrian-Detection-master/object_detection/meta_architectures/faster_rcnn_meta_arch.py", line 685, in _extract_rpn_feature_maps
preprocessed_inputs, scope=self.first_stage_feature_extractor_scope)
File "/home/mounir/PycharmProjects/Pedestrian-Detection-master/object_detection/meta_architectures/faster_rcnn_meta_arch.py", line 134, in extract_proposal_features
return self._extract_proposal_features(preprocessed_inputs, scope)
File "/home/mounir/PycharmProjects/Pedestrian-Detection-master/object_detection/models/faster_rcnn_inception_resnet_v2_feature_extractor.py", line 112, in _extract_proposal_features
align_feature_maps=True))
File "/home/mounir/PycharmProjects/Pedestrian-Detection-master/object_detection/nets/inception_resnet_v2.py", line 232, in inception_resnet_v2_base
scope='Conv2d_1a_3x3')
File "/home/mounir/anaconda3/envs/tflow-gpu/lib/python3.6/site-packages/tensorflow/contrib/framework/python/ops/arg_scope.py", line 183, in func_with_args
return func(*args, **current_args)
File "/home/mounir/anaconda3/envs/tflow-gpu/lib/python3.6/site-packages/tensorflow/contrib/layers/python/layers/layers.py", line 1154, in convolution2d
conv_dims=2)
File "/home/mounir/anaconda3/envs/tflow-gpu/lib/python3.6/site-packages/tensorflow/contrib/framework/python/ops/arg_scope.py", line 183, in func_with_args
return func(*args, **current_args)
File "/home/mounir/anaconda3/envs/tflow-gpu/lib/python3.6/site-packages/tensorflow/contrib/layers/python/layers/layers.py", line 1057, in convolution
outputs = layer.apply(inputs)
File "/home/mounir/anaconda3/envs/tflow-gpu/lib/python3.6/site-packages/tensorflow/python/keras/engine/base_layer.py", line 805, in apply
return self.call(inputs, *args, **kwargs)
File "/home/mounir/anaconda3/envs/tflow-gpu/lib/python3.6/site-packages/tensorflow/python/layers/base.py", line 362, in call
outputs = super(Layer, self).call(inputs, *args, **kwargs)
File "/home/mounir/anaconda3/envs/tflow-gpu/lib/python3.6/site-packages/tensorflow/python/keras/engine/base_layer.py", line 736, in call
outputs = self.call(inputs, *args, **kwargs)
File "/home/mounir/anaconda3/envs/tflow-gpu/lib/python3.6/site-packages/tensorflow/python/keras/layers/convolutional.py", line 186, in call
outputs = self._convolution_op(inputs, self.kernel)
File "/home/mounir/anaconda3/envs/tflow-gpu/lib/python3.6/site-packages/tensorflow/python/ops/nn_ops.py", line 868, in call
return self.conv_op(inp, filter)
File "/home/mounir/anaconda3/envs/tflow-gpu/lib/python3.6/site-packages/tensorflow/python/ops/nn_ops.py", line 520, in call
return self.call(inp, filter)
File "/home/mounir/anaconda3/envs/tflow-gpu/lib/python3.6/site-packages/tensorflow/python/ops/nn_ops.py", line 204, in call
name=self.name)
File "/home/mounir/anaconda3/envs/tflow-gpu/lib/python3.6/site-packages/tensorflow/python/ops/gen_nn_ops.py", line 956, in conv2d
data_format=data_format, dilations=dilations, name=name)
File "/home/mounir/anaconda3/envs/tflow-gpu/lib/python3.6/site-packages/tensorflow/python/framework/op_def_library.py", line 787, in _apply_op_helper
op_def=op_def)
File "/home/mounir/anaconda3/envs/tflow-gpu/lib/python3.6/site-packages/tensorflow/python/util/deprecation.py", line 454, in new_func
return func(*args, **kwargs)
File "/home/mounir/anaconda3/envs/tflow-gpu/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 3155, in create_op
op_def=op_def)
File "/home/mounir/anaconda3/envs/tflow-gpu/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 1717, in init
self._traceback = tf_stack.extract_stack()ResourceExhaustedError (see above for traceback): OOM when allocating tensor with shape[1,384,72,128] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
[[Node: FirstStageFeatureExtractor/InceptionResnetV2/InceptionResnetV2/Mixed_6a/Branch_1/Conv2d_1a_3x3/Conv2D = Conv2D[T=DT_FLOAT, data_format="NCHW", dilations=[1, 1, 1, 1], padding="SAME", strides=[1, 1, 1, 1], use_cudnn_on_gpu=true, _device="/job:localhost/replica:0/task:0/device:GPU:0"](FirstStageFeatureExtractor/InceptionResnetV2/InceptionResnetV2/Mixed_6a/Branch_1/Conv2d_0b_3x3/Relu, FirstStageFeatureExtractor/InceptionResnetV2/Mixed_6a/Branch_1/Conv2d_1a_3x3/weights/read/_3137)]]
Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.[[Node: gradients/SecondStageFeatureExtractor/InceptionResnetV2/Repeat/block8_9/Conv2d_1x1/Conv2D_grad/tuple/control_dependency_1/_5073 = _Recvclient_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device_incarnation=1, tensor_name="edge_13509...pendency_1", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:CPU:0"]]
Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/home/mounir/PycharmProjects/Pedestrian-Detection-master/object_detection/train.py", line 163, in
tf.app.run()
File "/home/mounir/anaconda3/envs/tflow-gpu/lib/python3.6/site-packages/tensorflow/python/platform/app.py", line 125, in run
_sys.exit(main(argv))
File "/home/mounir/PycharmProjects/Pedestrian-Detection-master/object_detection/train.py", line 159, in main
worker_job_name, is_chief, FLAGS.train_dir)
File "/home/mounir/PycharmProjects/Pedestrian-Detection-master/object_detection/trainer.py", line 332, in train
saver=saver)
File "/home/mounir/anaconda3/envs/tflow-gpu/lib/python3.6/site-packages/tensorflow/contrib/slim/python/slim/learning.py", line 785, in train
ignore_live_threads=ignore_live_threads)
File "/home/mounir/anaconda3/envs/tflow-gpu/lib/python3.6/contextlib.py", line 99, in exit
self.gen.throw(type, value, traceback)
File "/home/mounir/anaconda3/envs/tflow-gpu/lib/python3.6/site-packages/tensorflow/python/training/supervisor.py", line 1005, in managed_session
self.stop(close_summary_writer=close_summary_writer)
File "/home/mounir/anaconda3/envs/tflow-gpu/lib/python3.6/site-packages/tensorflow/python/training/supervisor.py", line 833, in stop
ignore_live_threads=ignore_live_threads)
File "/home/mounir/anaconda3/envs/tflow-gpu/lib/python3.6/site-packages/tensorflow/python/training/coordinator.py", line 389, in join
six.reraise(*self._exc_info_to_raise)
File "/home/mounir/anaconda3/envs/tflow-gpu/lib/python3.6/site-packages/six.py", line 693, in reraise
raise value
File "/home/mounir/anaconda3/envs/tflow-gpu/lib/python3.6/site-packages/tensorflow/python/training/coordinator.py", line 297, in stop_on_exception
yield
File "/home/mounir/anaconda3/envs/tflow-gpu/lib/python3.6/site-packages/tensorflow/python/training/coordinator.py", line 495, in run
self.run_loop()
File "/home/mounir/anaconda3/envs/tflow-gpu/lib/python3.6/site-packages/tensorflow/python/training/supervisor.py", line 1035, in run_loop
self._sv.global_step])
File "/home/mounir/anaconda3/envs/tflow-gpu/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 877, in run
run_metadata_ptr)
File "/home/mounir/anaconda3/envs/tflow-gpu/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1100, in _run
feed_dict_tensor, options, run_metadata)
File "/home/mounir/anaconda3/envs/tflow-gpu/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1272, in _do_run
run_metadata)
File "/home/mounir/anaconda3/envs/tflow-gpu/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1291, in _do_call
raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.ResourceExhaustedError: OOM when allocating tensor with shape[4,160,42,64] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
[[Node: FirstStageFeatureExtractor/InceptionResnetV2/InceptionResnetV2/Repeat_1/block17_2/Branch_1/Conv2d_0c_7x1/Conv2D-0-TransposeNHWCToNCHW-LayoutOptimizer = Transpose[T=DT_FLOAT, Tperm=DT_INT32, _device="/job:localhost/replica:0/task:0/device:GPU:0"](FirstStageFeatureExtractor/InceptionResnetV2/InceptionResnetV2/Repeat_1/block17_2/Branch_1/Conv2d_0c_7x1/SpaceToBatchND, PermConstNHWCToNCHW-LayoutOptimizer)]]
Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.[[Node: BatchMultiClassNonMaxSuppression/map/while/MultiClassNonMaxSuppression/strided_slice/_1871 = _Recvclient_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device_incarnation=1, tensor_name="edge_11146...ided_slice", tensor_type=DT_INT32, _device="/job:localhost/replica:0/task:0/device:CPU:0"]]
Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.Process finished with exit code 1
Would you have available the full pipeline.config file? It looks like it has been clipped in the blog post.
Hello, when I wsas using your model, I found that there was an error in creating the model, the response was [500], do you now what caused that? Thanks.
A declarative, efficient, and flexible JavaScript library for building user interfaces.
๐ Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. ๐๐๐
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google โค๏ธ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.