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Integrating Tensorflow object detection with keras cnn classifier


Integrating Tensorflow object detection with keras cnn classifier

By : Vladimir Grubor
Date : October 25 2020, 09:10 AM
I wish did fix the issue. This helps me to run the keras model inside the tensorflow SSD object Detection.
code :
* Use Seperate Graph.
* Use Seperate Session.
* reset the default Graph using tf.reset_default_graph()
* for keras Use K.clear

from keras.models import load_model
with tf.Session(graph=K.get_session().graph) as session:
    session.run(tf.global_variables_initializer())
    model = load_model('model.h5')
    predictions = model.predict(input)


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Create an object detection dataset for TensorFlow/Keras

Create an object detection dataset for TensorFlow/Keras


By : Ardonis Dalida Gonza
Date : March 29 2020, 07:55 AM
help you fix your problem A well known tool for labeling bounding box is labelImg: https://github.com/tzutalin/labelImg
To convert your dataset in TensorFlow format (I guess you mean tfrecord format), you can use a python script as this one: https://github.com/tensorflow/models/blob/master/research/object_detection/dataset_tools/create_pet_tf_record.py
Train an Object Detection Classifier How to Make Money with Tensorflow

Train an Object Detection Classifier How to Make Money with Tensorflow


By : Steve Band
Date : March 29 2020, 07:55 AM
should help you out After 7 hours of complete reinstallations and changing versions and updating pilotes and and and ... I had to look closely where is the import of calibration_pb2. And after 10 minutes of investigations, I noticed that the protoc cmd does not generate the file calibration_pb2.py !!!!
To generate the file calibration_pb2.py
code :
protoc --python_out=. .\object_detection\protos\anchor_generator.proto .\object_detection\protos\argmax_matcher.proto .\object_detection\protos\bipartite_matcher.proto .\object_detection\protos\box_coder.proto .\object_detection\protos\box_predictor.proto .\object_detection\protos\eval.proto .\object_detection\protos\faster_rcnn.proto .\object_detection\protos\faster_rcnn_box_coder.proto .\object_detection\protos\grid_anchor_generator.proto .\object_detection\protos\hyperparams.proto .\object_detection\protos\image_resizer.proto .\object_detection\protos\input_reader.proto .\object_detection\protos\losses.proto .\object_detection\protos\matcher.proto .\object_detection\protos\mean_stddev_box_coder.proto .\object_detection\protos\model.proto .\object_detection\protos\optimizer.proto .\object_detection\protos\pipeline.proto .\object_detection\protos\post_processing.proto .\object_detection\protos\preprocessor.proto .\object_detection\protos\region_similarity_calculator.proto .\object_detection\protos\square_box_coder.proto .\object_detection\protos\ssd.proto .\object_detection\protos\ssd_anchor_generator.proto .\object_detection\protos\string_int_label_map.proto .\object_detection\protos\train.proto .\object_detection\protos\keypoint_box_coder.proto .\object_detection\protos\multiscale_anchor_generator.proto .\object_detection\protos\graph_rewriter.proto
protoc --python_out=. .\object_detection\protos\anchor_generator.proto .\object_detection\protos\argmax_matcher.proto .\object_detection\protos\bipartite_matcher.proto .\object_detection\protos\box_coder.proto .\object_detection\protos\box_predictor.proto .\object_detection\protos\eval.proto .\object_detection\protos\faster_rcnn.proto .\object_detection\protos\faster_rcnn_box_coder.proto .\object_detection\protos\grid_anchor_generator.proto .\object_detection\protos\hyperparams.proto .\object_detection\protos\image_resizer.proto .\object_detection\protos\input_reader.proto .\object_detection\protos\losses.proto .\object_detection\protos\matcher.proto .\object_detection\protos\mean_stddev_box_coder.proto .\object_detection\protos\model.proto .\object_detection\protos\optimizer.proto .\object_detection\protos\pipeline.proto .\object_detection\protos\post_processing.proto .\object_detection\protos\preprocessor.proto .\object_detection\protos\region_similarity_calculator.proto .\object_detection\protos\square_box_coder.proto .\object_detection\protos\ssd.proto .\object_detection\protos\ssd_anchor_generator.proto .\object_detection\protos\string_int_label_map.proto .\object_detection\protos\train.proto .\object_detection\protos\keypoint_box_coder.proto .\object_detection\protos\multiscale_anchor_generator.proto .\object_detection\protos\graph_rewriter.proto .\object_detection\protos\calibration.proto
object detection using tensorflow by own classifier

object detection using tensorflow by own classifier


By : Quicksilver
Date : March 29 2020, 07:55 AM
I wish this help you I've managed to solve this problem in my system (windows 10). The solution is not very straight forward but:
1) First u need to clone Tensorflow Object Detection API repository https://github.com/tensorflow/models.
when training object detection classifier --> ImportError: No module named tensorflow

when training object detection classifier --> ImportError: No module named tensorflow


By : Pemmaraju5
Date : March 29 2020, 07:55 AM
wish help you to fix your issue try pip freeze if you don't find tensorflow in list then install using below command.
code :
pip install --upgrade tensorflow
Image Classifier with Tensorflow and Keras

Image Classifier with Tensorflow and Keras


By : Valerio
Date : March 29 2020, 07:55 AM
hop of those help? Since you are a beginner, you may not know that you actually do not need to retrain the model in order to test :D. Your hunch is right, and we will see down below how you can do that.
You can save the weights of your model in a specific file format. In Keras, it is a file with the extension .hdf5.
code :
from tensorflow.keras.models import load_model


##Do some stuff, train model

model.save(model_name)

##Do some stuff

loaded_model = load_model(model_name)
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