f4334277
 Hu Chunming
提交3rdparty
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import numpy as np
import sys
import os
import argparse
import tensorflow as tf
from tensorflow.python.platform import gfile
from imagenet_cls_test_alexnet import MeanValueFetch, DnnCaffeModel, Framework, ClsAccEvaluation
try:
import cv2 as cv
except ImportError:
raise ImportError('Can\'t find OpenCV Python module. If you\'ve built it from sources without installation, '
'configure environment variable PYTHONPATH to "opencv_build_dir/lib" directory (with "python3" subdirectory if required)')
# If you've got an exception "Cannot load libmkl_avx.so or libmkl_def.so" or similar, try to export next variable
# before running the script:
# LD_PRELOAD=/opt/intel/mkl/lib/intel64/libmkl_core.so:/opt/intel/mkl/lib/intel64/libmkl_sequential.so
class TensorflowModel(Framework):
sess = tf.Session
output = tf.Graph
def __init__(self, model_file, in_blob_name, out_blob_name):
self.in_blob_name = in_blob_name
self.sess = tf.Session()
with gfile.FastGFile(model_file, 'rb') as f:
graph_def = tf.GraphDef()
graph_def.ParseFromString(f.read())
self.sess.graph.as_default()
tf.import_graph_def(graph_def, name='')
self.output = self.sess.graph.get_tensor_by_name(out_blob_name + ":0")
def get_name(self):
return 'Tensorflow'
def get_output(self, input_blob):
assert len(input_blob.shape) == 4
batch_tf = input_blob.transpose(0, 2, 3, 1)
out = self.sess.run(self.output,
{self.in_blob_name+':0': batch_tf})
out = out[..., 1:1001]
return out
class DnnTfInceptionModel(DnnCaffeModel):
net = cv.dnn.Net()
def __init__(self, model_file, in_blob_name, out_blob_name):
self.net = cv.dnn.readNetFromTensorflow(model_file)
self.in_blob_name = in_blob_name
self.out_blob_name = out_blob_name
def get_output(self, input_blob):
return super(DnnTfInceptionModel, self).get_output(input_blob)[..., 1:1001]
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("--imgs_dir", help="path to ImageNet validation subset images dir, ILSVRC2012_img_val dir")
parser.add_argument("--img_cls_file", help="path to file with classes ids for images, download it here:"
"https://github.com/opencv/opencv_extra/tree/master/testdata/dnn/img_classes_inception.txt")
parser.add_argument("--model", help="path to tensorflow model, download it here:"
"https://storage.googleapis.com/download.tensorflow.org/models/inception5h.zip")
parser.add_argument("--log", help="path to logging file")
parser.add_argument("--batch_size", help="size of images in batch", default=1)
parser.add_argument("--frame_size", help="size of input image", default=224)
parser.add_argument("--in_blob", help="name for input blob", default='input')
parser.add_argument("--out_blob", help="name for output blob", default='softmax2')
args = parser.parse_args()
data_fetcher = MeanValueFetch(args.frame_size, args.imgs_dir, True)
frameworks = [TensorflowModel(args.model, args.in_blob, args.out_blob),
DnnTfInceptionModel(args.model, '', args.out_blob)]
acc_eval = ClsAccEvaluation(args.log, args.img_cls_file, args.batch_size)
acc_eval.process(frameworks, data_fetcher)
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