-
Notifications
You must be signed in to change notification settings - Fork 156
/
convert.py
75 lines (61 loc) · 2.08 KB
/
convert.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
import sys
from rknn.api import RKNN
DATASET_PATH = '../../../datasets/COCO/coco_subset_20.txt'
DEFAULT_RKNN_PATH = '../model/yolov5.rknn'
DEFAULT_QUANT = True
def parse_arg():
if len(sys.argv) < 3:
print("Usage: python3 {} onnx_model_path [platform] [dtype(optional)] [output_rknn_path(optional)]".format(sys.argv[0]))
print(" platform choose from [rk3562,rk3566,rk3568,rk3588,rk1808,rv1109,rv1126]")
print(" dtype choose from [i8, fp] for [rk3562,rk3566,rk3568,rk3588]")
print(" dtype choose from [u8, fp] for [rk1808,rv1109,rv1126]")
exit(1)
model_path = sys.argv[1]
platform = sys.argv[2]
do_quant = DEFAULT_QUANT
if len(sys.argv) > 3:
model_type = sys.argv[3]
if model_type not in ['i8', 'u8', 'fp']:
print("ERROR: Invalid model type: {}".format(model_type))
exit(1)
elif model_type in ['i8', 'u8']:
do_quant = True
else:
do_quant = False
if len(sys.argv) > 4:
output_path = sys.argv[4]
else:
output_path = DEFAULT_RKNN_PATH
return model_path, platform, do_quant, output_path
if __name__ == '__main__':
model_path, platform, do_quant, output_path = parse_arg()
# Create RKNN object
rknn = RKNN(verbose=False)
# Pre-process config
print('--> Config model')
rknn.config(mean_values=[[0, 0, 0]], std_values=[
[255, 255, 255]], target_platform=platform)
print('done')
# Load model
print('--> Loading model')
ret = rknn.load_onnx(model=model_path)
if ret != 0:
print('Load model failed!')
exit(ret)
print('done')
# Build model
print('--> Building model')
ret = rknn.build(do_quantization=do_quant, dataset=DATASET_PATH)
if ret != 0:
print('Build model failed!')
exit(ret)
print('done')
# Export rknn model
print('--> Export rknn model')
ret = rknn.export_rknn(output_path)
if ret != 0:
print('Export rknn model failed!')
exit(ret)
print('done')
# Release
rknn.release()