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Import SSDs from TensorFlow by training config (#12188)

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* Remove TensorFlow and protobuf dependencies from object detection scripts

* Create text graphs for TensorFlow object detection networks from sample
This commit is contained in:
Dmitry Kurtaev
2018-09-03 17:08:40 +03:00
committed by Vadim Pisarevsky
parent e3af72bb68
commit c7cf8fb35c
10 changed files with 858 additions and 450 deletions
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samples/dnn/object_detection.py
+25 -3
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@@ -3,6 +3,10 @@ import argparse
import sys
import numpy as np
from tf_text_graph_common import readTextMessage
from tf_text_graph_ssd import createSSDGraph
from tf_text_graph_faster_rcnn import createFasterRCNNGraph
backends = (cv.dnn.DNN_BACKEND_DEFAULT, cv.dnn.DNN_BACKEND_HALIDE, cv.dnn.DNN_BACKEND_INFERENCE_ENGINE, cv.dnn.DNN_BACKEND_OPENCV)
targets = (cv.dnn.DNN_TARGET_CPU, cv.dnn.DNN_TARGET_OPENCL, cv.dnn.DNN_TARGET_OPENCL_FP16, cv.dnn.DNN_TARGET_MYRIAD)
@@ -11,11 +15,15 @@ parser.add_argument('--input', help='Path to input image or video file. Skip thi
parser.add_argument('--model', required=True,
help='Path to a binary file of model contains trained weights. '
'It could be a file with extensions .caffemodel (Caffe), '
'.pb (TensorFlow), .t7 or .net (Torch), .weights (Darknet)')
'.pb (TensorFlow), .t7 or .net (Torch), .weights (Darknet), .bin (OpenVINO)')
parser.add_argument('--config',
help='Path to a text file of model contains network configuration. '
'It could be a file with extensions .prototxt (Caffe), .pbtxt (TensorFlow), .cfg (Darknet)')
parser.add_argument('--framework', choices=['caffe', 'tensorflow', 'torch', 'darknet'],
'It could be a file with extensions .prototxt (Caffe), .pbtxt or .config (TensorFlow), .cfg (Darknet), .xml (OpenVINO)')
parser.add_argument('--out_tf_graph', default='graph.pbtxt',
help='For models from TensorFlow Object Detection API, you may '
'pass a .config file which was used for training through --config '
'argument. This way an additional .pbtxt file with TensorFlow graph will be created.')
parser.add_argument('--framework', choices=['caffe', 'tensorflow', 'torch', 'darknet', 'dldt'],
help='Optional name of an origin framework of the model. '
'Detect it automatically if it does not set.')
parser.add_argument('--classes', help='Optional path to a text file with names of classes to label detected objects.')
@@ -46,6 +54,20 @@ parser.add_argument('--target', choices=targets, default=cv.dnn.DNN_TARGET_CPU,
'%d: VPU' % targets)
args = parser.parse_args()
# If config specified, try to load it as TensorFlow Object Detection API's pipeline.
config = readTextMessage(args.config)
if 'model' in config:
print('TensorFlow Object Detection API config detected')
if 'ssd' in config['model'][0]:
print('Preparing text graph representation for SSD model: ' + args.out_tf_graph)
createSSDGraph(args.model, args.config, args.out_tf_graph)
args.config = args.out_tf_graph
elif 'faster_rcnn' in config['model'][0]:
print('Preparing text graph representation for Faster-RCNN model: ' + args.out_tf_graph)
createFasterRCNNGraph(args.model, args.config, args.out_tf_graph)
args.config = args.out_tf_graph
# Load names of classes
classes = None
if args.classes: