-
Notifications
You must be signed in to change notification settings - Fork 477
/
Copy pathtest_yolov7face.py
142 lines (114 loc) · 5.33 KB
/
test_yolov7face.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from fastdeploy import ModelFormat
import fastdeploy as fd
import cv2
import os
import pickle
import numpy as np
import runtime_config as rc
def test_detection_yolov7face():
model_url = "https://bj.bcebos.com/paddlehub/fastdeploy/yolov7-lite-e.onnx"
input_url1 = "https://gitee.com/paddlepaddle/PaddleDetection/raw/release/2.4/demo/000000014439.jpg"
input_url2 = "https://gitee.com/paddlepaddle/PaddleDetection/raw/release/2.4/demo/000000570688.jpg"
result_url1 = "https://bj.bcebos.com/paddlehub/fastdeploy/yolov7face_result1.pkl"
result_url2 = "https://bj.bcebos.com/paddlehub/fastdeploy/yolov7face_result2.pkl"
fd.download(model_url, "resources")
fd.download(input_url1, "resources")
fd.download(input_url2, "resources")
fd.download(result_url1, "resources")
fd.download(result_url2, "resources")
model_file = "resources/yolov7-lite-e.onnx"
model = fd.vision.facedet.YOLOv7Face(
model_file, runtime_option=rc.test_option)
model.postprocessor.conf_threshold = 0.3
with open("resources/yolov7face_result1.pkl", "rb") as f:
expect1 = pickle.load(f)
with open("resources/yolov7face_result2.pkl", "rb") as f:
expect2 = pickle.load(f)
im1 = cv2.imread("./resources/000000014439.jpg")
im2 = cv2.imread("./resources/000000570688.jpg")
for i in range(3):
# test single predict
result1 = model.predict(im1)
result2 = model.predict(im2)
diff_boxes_1 = np.fabs(
np.array(result1.boxes) - np.array(expect1["boxes"]))
diff_boxes_2 = np.fabs(
np.array(result2.boxes) - np.array(expect2["boxes"]))
diff_scores_1 = np.fabs(
np.array(result1.scores) - np.array(expect1["scores"]))
diff_scores_2 = np.fabs(
np.array(result2.scores) - np.array(expect2["scores"]))
assert diff_boxes_1.max(
) < 1e-03, "There's difference in detection boxes 1."
assert diff_scores_1.max(
) < 1e-04, "There's difference in detection score 1."
assert diff_boxes_2.max(
) < 1e-03, "There's difference in detection boxes 2."
assert diff_scores_2.max(
) < 1e-04, "There's difference in detection score 2."
# test batch predict
results = model.batch_predict([im1, im2])
result1 = results[0]
result2 = results[1]
diff_boxes_1 = np.fabs(
np.array(result1.boxes) - np.array(expect1["boxes"]))
diff_boxes_2 = np.fabs(
np.array(result2.boxes) - np.array(expect2["boxes"]))
diff_scores_1 = np.fabs(
np.array(result1.scores) - np.array(expect1["scores"]))
diff_scores_2 = np.fabs(
np.array(result2.scores) - np.array(expect2["scores"]))
assert diff_boxes_1.max(
) < 1e-03, "There's difference in detection boxes 1."
assert diff_scores_1.max(
) < 1e-04, "There's difference in detection score 1."
assert diff_boxes_2.max(
) < 1e-03, "There's difference in detection boxes 2."
assert diff_scores_2.max(
) < 1e-04, "There's difference in detection score 2."
def test_detection_yolov7face_runtime():
model_url = "https://bj.bcebos.com/paddlehub/fastdeploy/yolov7-lite-e.onnx"
input_url1 = "https://gitee.com/paddlepaddle/PaddleDetection/raw/release/2.4/demo/000000014439.jpg"
result_url1 = "https://bj.bcebos.com/paddlehub/fastdeploy/yolov7_result1.pkl"
fd.download(model_url, "resources")
fd.download(input_url1, "resources")
fd.download(result_url1, "resources")
model_file = "resources/yolov7-lite-e.onnx"
preprocessor = fd.vision.detection.Yolov7FacePreprocessor()
postprocessor = fd.vision.detection.YOLOv7FacePostprocessor()
rc.test_option.set_model_path(model_file, model_format=ModelFormat.ONNX)
rc.test_option.use_openvino_backend()
runtime = fd.Runtime(rc.test_option)
with open("resources/yolov7_result1.pkl", "rb") as f:
expect1 = pickle.load(f)
im1 = cv2.imread("resources/000000014439.jpg")
for i in range(3):
# test runtime
input_tensors, ims_info = preprocessor.run([im1.copy()])
output_tensors = runtime.infer({"images": input_tensors[0]})
results = postprocessor.run(output_tensors, ims_info)
result1 = results[0]
diff_boxes_1 = np.fabs(
np.array(result1.boxes) - np.array(expect1["boxes"]))
diff_scores_1 = np.fabs(
np.array(result1.scores) - np.array(expect1["scores"]))
assert diff_boxes_1.max(
) < 1e-03, "There's difference in detection boxes 1."
assert diff_scores_1.max(
) < 1e-04, "There's difference in detection score 1."
if __name__ == "__main__":
test_detection_yolov7face()
test_detection_yolov7face_runtime()