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Save NobuoTsukamoto/ac670e1103d58ef77d5f5db284bf43b7 to your computer and use it in GitHub Desktop.
Thank you for the posting.
I have been trying to run to the end of "ssd_mobilenet_v3_small_coco_2020_01_14" on my Centos7 conda env (Py3.6 TF1.12). I get to the code cell starting with "run_detection" but get a serious error stating*
InvalidArgumentError in import_graph_def(graph_def, input_map, return_elements, name, op_dict, producer_op_list)
In my environment I find, print(tf.graph_util.import_graph_def.doc) sayingSOME ARGUMENTS ARE DEPRECATED. They will be removed in a future version.
Instructions for updating:
Please file an issue at https://github.com/tensorflow/tensorflow/issues if you depend on this feature.
I don't find any instruction in the url.
Please help me to fix this issue.
InvalidArgumentError in import_graph_def(graph_def, input_map, return_elements, name, op_dict, producer_op_list)
Problem is the graph has been compiled for a different version of Tensorflow ( May be TF1.14 or above ). But, graphs cannot be compiled with TF1.12 ( and TF1.13 ). export_inference_graph.py results in an error and freeze graph cannot be executed. Please run with the latest TF1.15.x.
Sorry to ask a trivial question:
I changed TF to 1.15.3. But something else bothers me. The problem seems to come from package name registration in Jupyter notebook.
To be specific, I got an error saying:
ImportError: cannot import name 'anchor_generator_pb2' I thought I am in the directory I have prepared.
os.getcwd() > '/home/kamae/Desktop/NTTGCPGithub/models/research'
However import below seems not to work
from object_detection.protos import eval_pb2
I broke down to two steps to get working
import object_detection.protos
from protos import eval_pb2
I am using python3.6.8 and tf1.15.3 setup by conda envs
Thank you.
Please check the installation.
https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/installation.md
Is the Protobuf libraries installed?
https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/installation.md#protobuf-compilation
If installed, the following commands will not show any errors.
# From tensorflow/models/research/
protoc object_detection/protos/*.proto --python_out=.
If an error occurs, please install or build.
https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/installation.md#manual-protobuf-compiler-installation-and-usage
@kamae さん
すいません。少し質問させてください(難しいところもあり、日本語でお願いします)。
- "a custum COCO-like dataset"は、ご自身が作成したデータセットでしょうか?または、公開されているデータセットでしょうか?学習に必要なTF-Recodeの作成のハードルが高いと思います。TF-Recodeの作成が必要な場合、create_coco_tf_record.pyをベースに改造が必要と思います。公開されているデータセットであれば手順を示しやすいのです。ご自身が作成した場合、使用したツールの情報があればとは思います。
- 私はAndroidのアプリには詳しくはありません。TensorFlow Lite Object Detection Android Demoを参考にモデルを入れ替えることぐらいとなります。
既にご存知かもしれませんが、
- SSD_MobileNetV3を使用するには、最新のtensorflow/modelsのリポジトリを使用してください。
- 公開されているpre-trained modelには問題(Largeでオブジェクトを検出しない)があります。新しいpre-trained modelへのurlはまだマージされていません。こちらのPull Requestのdownload urlを参考にしてください。なお、このnotebookでのリンクは新しいdownload urlに修正してあります。
_ was confused about which packages are called. i think I sorted the paths out. Now I am stack by the following error.
File "/home/kamae/Desktop/NTTGCPGithub/models/research/object_detection/builders/model_builder.py", line 179, in _build_ssd_feature_extractor
raise ValueError('Unknown ssd feature_extractor: {}'.format(feature_type))
ValueError: Unknown ssd feature_extractor: ssd_mobilenet_v3_small
Will someone kindly direct me to a new model_builder.py that has an entry for ssd_mobilenet_v3_small/large?
@kamae san
Check SSD_FEATURE_EXTRACTOR_CLASS_MAP in models/research/object_detection/builders/model_builder.py.
For the latest master repository, ssd_mobilenet_v3_small and ssd_mobilenet_v3_large are defined as follows. If not, clone the latest repository.
# A map of names to SSD feature extractors.
SSD_FEATURE_EXTRACTOR_CLASS_MAP = {
'ssd_inception_v2': SSDInceptionV2FeatureExtractor,
'ssd_inception_v3': SSDInceptionV3FeatureExtractor,
'ssd_mobilenet_v1': SSDMobileNetV1FeatureExtractor,
'ssd_mobilenet_v1_fpn': SSDMobileNetV1FpnFeatureExtractor,
'ssd_mobilenet_v1_ppn': SSDMobileNetV1PpnFeatureExtractor,
'ssd_mobilenet_v2': SSDMobileNetV2FeatureExtractor,
'ssd_mobilenet_v2_fpn': SSDMobileNetV2FpnFeatureExtractor,
'ssd_mobilenet_v3_large': SSDMobileNetV3LargeFeatureExtractor,
'ssd_mobilenet_v3_small': SSDMobileNetV3SmallFeatureExtractor,
'ssd_mobilenet_edgetpu': SSDMobileNetEdgeTPUFeatureExtractor,
'ssd_resnet50_v1_fpn': ssd_resnet_v1_fpn.SSDResnet50V1FpnFeatureExtractor,
'ssd_resnet101_v1_fpn': ssd_resnet_v1_fpn.SSDResnet101V1FpnFeatureExtractor,
'ssd_resnet152_v1_fpn': ssd_resnet_v1_fpn.SSDResnet152V1FpnFeatureExtractor,
'ssd_resnet50_v1_ppn': ssd_resnet_v1_ppn.SSDResnet50V1PpnFeatureExtractor,
'ssd_resnet101_v1_ppn':
ssd_resnet_v1_ppn.SSDResnet101V1PpnFeatureExtractor,
'ssd_resnet152_v1_ppn':
ssd_resnet_v1_ppn.SSDResnet152V1PpnFeatureExtractor,
'embedded_ssd_mobilenet_v1': EmbeddedSSDMobileNetV1FeatureExtractor,
'ssd_pnasnet': SSDPNASNetFeatureExtractor,
}
Hi! Thanks for the notebook! It works great before the large model. It seems that the large model has some bug. There's no bbox on the bottom images.