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License: Apache License 2.0
The repo to host all the web data including images for documents in dmlc projects.
License: Apache License 2.0
I want to learn the difference between this darknet and the original darknet( https://pjreddie.com/darknet/yolo/). How can get the source code of libdarknet.so?
I'm sorry for my poor English, and thanks for you help!
hi, guys,
any guys can point out how to use tensorflow pre-trained object detection model?
I checked the doc, it seems just TVM support classification for tensorflow framework.
now I want to use pre-trained model for tensorflow (for example faster_rcnn_resnet101_coco_2018_01_28.tar.gz or ssd_mobilenet_v1_coco_11_06_2017.tar.bz2), and used script "tvm/tutorials/nnvm/from_tensorflow.py" with some modification (just point to these pre-trained models).
but I get some errors:
Traceback (most recent call last):
File "from_tensorflow.py", line 98, in
graph_def = nnvm.testing.tf.AddShapesToGraphDef(sess, 'softmax')
File "/root/ai/tvm/nnvm/python/nnvm/testing/tf.py", line 70, in AddShapesToGraphDef
[out_node],
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/graph_util_impl.py", line 227, in convert_variables_to_constants
inference_graph = extract_sub_graph(input_graph_def, output_node_names)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/graph_util_impl.py", line 171, in extract_sub_graph
_assert_nodes_are_present(name_to_node, dest_nodes)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/graph_util_impl.py", line 131, in _assert_nodes_are_present
assert d in name_to_node, "%s is not in graph" % d
AssertionError: softmax is not in graph
if I comment out following codes,
" with tf.Session() as sess:
graph_def = nnvm.testing.tf.AddShapesToGraphDef(sess, 'softmax')"
and get below errors:
Traceback (most recent call last):
File "from_tensorflow.py", line 123, in
sym, params = nnvm.frontend.from_tensorflow(graph_def)
File "/root/ai/tvm/nnvm/python/nnvm/frontend/tensorflow.py", line 1503, in from_tensorflow
sym, params = g.from_tensorflow(graph, layout, shape, outputs)
File "/root/ai/tvm/nnvm/python/nnvm/frontend/tensorflow.py", line 1163, in from_tensorflow
"The following operators are not implemented: {}".format(missing_operators))
NotImplementedError: The following operators are not implemented: set([u'Slice', u'TopKV2', u'Sqrt', u'CropAndResize', u'Exit', u'Tile', u'TensorArrayGatherV3', u'Max', u'NonMaxSuppressionV2', u'LogicalAnd', u'Assert', u'TensorArraySizeV3', u'TensorArrayWriteV3', u'TensorArrayReadV3', u'All', u'LoopCond', u'Merge', u'Switch', u'Exp', u'Enter', u'Where', u'Round', u'NextIteration', u'TensorArrayV3', u'TensorArrayScatterV3', u'ZerosLike', u'Select', u'Size'])
when i am try to test a new pic on this pre trained frcnn but this give me error and not accepting any kind of image other than this
I am trying to optimise yolov3-tiny darknet model on jetson nano using TVM compiler. I tried to run the code as mentioned in the below URL.
https://docs.tvm.ai/tutorials/frontend/from_darknet.html#sphx-glr-tutorials-frontend-from-darknet-py
It was throwing errors to download the weight and cfg files.So,I downloaded separately and gave the corresponding path.For downloading the darknet library it is throwing an error saying 'nonetype' content length in the url headers. Attached the screenshot below.
Can anyone help me in solving this issue??
I have also tried to download "libdarnet2.so" separately from the url and and tried to load.This time I am getting the error telling "cannot open shared object file.Additionally, "ctypes.util.find_library() did not manage to locate a library called libdarnet2.so" even though I mentioned the correct path for loading.
I am trying to create a TVM unit-test with BERT base, and I noticed that other .pb files used in unit tests are uploaded here. I created the model .pb, created a fork of this repo, but am unable to push to my remote branch because it exceeds GitHub's max file size of 100MB. The BERT .pb is 679MB. Is there any way around this? It would be really nice to add a BERT test in TVM.
@srkreddy1238 @tqchen do you have any thoughts?
Thanks!
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