-
Notifications
You must be signed in to change notification settings - Fork 1
/
Copy pathrun_detection_infer.py
337 lines (274 loc) · 12.6 KB
/
run_detection_infer.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
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
#!/usr/bin/env python
# -*- coding: UTF-8 -*-
# @Project ：ppdettorch
# @File ：run_detection_infer.py
# @Author ：sl
# @Date ：2022/11/7 18:23
from ppdettorch.utils.logger_utils import logger
from ppdettorch.utils.detection_infer_utils import DetectionInferUtils
from ppdettorch.utils.file_utils import FileUtils
from ppdettorch.utils.time_utils import TimeUtils
from ppdettorch.process.infer.detection_predict import main as main_detection
from ppdettorch.utils.constant import Constants
"""
检测 推理
https://bj.bcebos.com/v1/paddledet/models/keypoint/tinypose_enhance/picodet_s_192_lcnet_pedestrian.pdparams
"""
class DetectionRunInfer(object):
def __init__(self):
self.base_dir_image = f"{Constants.DATA_DIR}/ocr/imgs_words/ch"
self.run_time = TimeUtils.now_str_short()
self.base_dir = Constants.WORK_DIR
self.detection_config_dir = f"{Constants.WORK_DIR}/configs"
self.checkpoint_base_url = "https://paddledet.bj.bcebos.com/models"
self.checkpoint_base_url_paddledet = "https://bj.bcebos.com/v1/paddledet/models"
self.checkpoint_base_url_ppstructure = "https://paddleocr.bj.bcebos.com/ppstructure/models/layout/"
self.checkpoint_base_url_pedestrian = "https://bj.bcebos.com/v1/paddledet/models/keypoint/tinypose_enhance/"
# self.checkpoint_base_url = "~/.cache/paddle/weights/"
def run_picodet_coco_model(self, config_file=None, do_transform=True):
"""
测试 picodet
:param config_file:
:param do_transform:
:return:
"""
# config_file = f"{self.base_dir}/configs/picodet/{config_name}.yml"
model_name = FileUtils.get_file_name(config_file)
layout_zh = False
predict_labels = None
if model_name in ["picodet_lcnet_x1_0_layout", ]:
layout_zh = True
base_url = self.checkpoint_base_url_ppstructure
predict_labels = "~/PaddleOCR/ppocr/utils/dict/layout_dict/layout_cdla_dict.txt"
elif model_name in ["picodet_s_192_pedestrian", "picodet_s_320_pedestrian",
"picodet_s_192_lcnet_pedestrian", "picodet_s_320_lcnet_pedestrian"]:
base_url = self.checkpoint_base_url_pedestrian
# model_name = str(model_name).replace("_pedestrian", "_pedestrian")
elif model_name in ['retinanet_r50_fpn_2x_coco']:
base_url = self.checkpoint_base_url
model_name = "retinanet_r101_distill_r50_2x_coco"
elif model_name in ["rtdetr_r34vd_6x_coco", "rtdetr_r18vd_6x_coco"]:
base_url = self.checkpoint_base_url_paddledet
else:
base_url = self.checkpoint_base_url
# model param name replace
model_params_config = {
"rtdetr_r34vd_6x_coco": "rtdetr_r34vd_dec4_6x_coco",
"rtdetr_r18vd_6x_coco": "rtdetr_r18vd_dec3_6x_coco",
}
if layout_zh:
checkpoint_file = f"{base_url}/picodet_lcnet_x1_0_fgd_layout_cdla.pdparams"
elif model_name in model_params_config.keys():
checkpoint_file = f"{base_url}/{model_params_config.get(model_name, model_name)}.pdparams"
else:
checkpoint_file = f"{base_url}/{model_name}.pdparams"
# picodet_lcnet_x1_0_fgd_layout_cdla.pdparams
# picodet_lcnet_x1_0_fgd_layout.pdparams
# checkpoint_file = f"{self.checkpoint_base_url}/{config_name}.pth"
run_arg = DetectionInferUtils.init_args()
run_arg.config = config_file
run_arg.opt = {
"use_gpu": True,
"weights": checkpoint_file
}
if layout_zh:
run_arg.opt["num_classes"] = 10
run_arg.infer_img = f"{self.base_dir}/demo/000000014439.jpg"
# run_arg.infer_img = f"{self.base_dir}/demo/car.jpg"
# run_arg.infer_img = f"{self.base_dir}/docs/images/layout.jpg"
# run_arg.infer_img = f"{self.base_dir}/docs/images/layout_demo2.png"
# run_arg.infer_img = f"{Constants.USER_HOME}/ocr/PaddleOCR/ppstructure/docs/table/layout_demo2.png"
run_arg.predict_labels = predict_labels
model_class = self.get_model_class(config_file)
run_arg.output_dir = f"{Constants.OUTPUT_MODELS_DIR}/detection/{model_class}/{model_name}/inference_results/{self.run_time}"
run_arg.do_transform = do_transform
main_detection(run_arg)
def get_model_class(self, config_file):
begin_index = len(f"{self.detection_config_dir}/")
config_name = config_file[begin_index:]
end_index = config_name.find("/")
model_class = config_name[:end_index]
return model_class
def run_picodet_coco(self, config_name=None):
"""
测试 picodet
:return:
"""
# picodet
config_name = "picodet_s_320_coco"
config_name = "picodet_s_416_coco"
config_name = "picodet_m_320_coco"
config_name = "picodet_m_416_coco"
config_name = "picodet_l_320_coco"
config_name = "picodet_l_416_coco"
config_name = "picodet_l_640_coco"
config_name = "/more_config/picodet_lcnet_1_5x_416_coco"
config_name = "/more_config/picodet_lcnet_1_5x_640_coco"
config_name = "/more_config/picodet_shufflenetv2_1x_416_coco"
config_name = "/more_config/picodet_mobilenetv3_large_1x_416_coco.yml"
config_name = "/more_config/picodet_r18_640_coco.yml"
config_name = "/application/layout_analysis/picodet_lcnet_x1_0_layout.yml"
# config_name = "/application/layout_analysis/picodet_lcnet_x2_5_layout.yml"
# config_name = "/application/mainbody_detection/picodet_lcnet_x2_5_640_mainbody.yml"
# config_name = "/application/pedestrian_detection/picodet_s_192_pedestrian.yml"
# config_name = "/application/pedestrian_detection/picodet_s_320_pedestrian.yml"
# config_name = "/application/pedestrian_detection/picodet_s_192_lcnet_pedestrian.yml"
# config_name = "/application/pedestrian_detection/picodet_s_320_lcnet_pedestrian.yml"
# ppyoloe
# config_name = "ppyoloe_crn_s_300e_coco.yml"
# yolox
# config_name = "yolox_s_300e_coco.yml"
# yolov3
# config_name = "yolov3_mobilenet_v1_270e_coco.yml"
# config_name = "yolov3_mobilenet_v3_large_270e_coco.yml"
# config_name = "yolov3_darknet53_270e_coco.yml"
# # yolov5
# config_name = "yolov5_s_300e_coco.yml"
#
# # convnext
# config_name = "yolov5_convnext_s_36e_coco.yml"
# config_name = "yolox_convnext_s_36e_coco.yml"
# config_name = "ppyoloe_convnext_tiny_36e_coco.yml"
# # yolov6
# config_name = "yolov6_n_300e_coco.yml"
# config_name = "yolov6_s_300e_coco.yml"
# config_name = "yolov6_m_300e_coco.yml"
config_name = "yolov6_l_300e_coco.yml"
# config_name = "yolov6lite/yolov6lite_s_400e_coco.yml"
# config_name = "yolov6lite/yolov6lite_m_400e_coco.yml"
# config_name = "yolov6lite/yolov6lite_l_400e_coco.yml"
# # yolov7
# config_name = "yolov7_l_300e_coco.yml"
#
# # rtmdet
# config_name = "rtmdet_s_300e_coco.yml"
# yolov8
# config_name = f"yolov8_n_500e_coco.yml"
# ssd
# config_name = f"ssd_mobilenet_v1_300_120e_voc.yml"
# config_name = f"ssd_vgg16_300_240e_voc.yml"
# config_name = f"ssdlite_mobilenet_v3_large_320_coco.yml"
# config_name = f"ssdlite_mobilenet_v3_small_320_coco.yml"
# centernet
# config_name = f"centernet_mbv1_140e_coco.yml"
# blazeface
# config_name = f"blazeface_1000e.yml"
# config_name = f"blazeface_fpn_ssh_1000e.yml"
# retinanet
# config_name = f"retinanet_r50_fpn_1x_coco.yml"
# config_name = f"retinanet_r101_fpn_2x_coco.yml"
# config_name = f"retinanet_r50_fpn_2x_coco.yml"
# rtdetr
# config_name = f"rtdetr_r50vd_6x_coco.yml"
# config_name = f"rtdetr_r101vd_6x_coco.yml"
# config_name = f"rtdetr_hgnetv2_l_6x_coco.yml"
# config_name = f"rtdetr_hgnetv2_x_6x_coco.yml"
# config_name = f"rtdetr_r50vd_m_6x_coco.yml"
# config_name = f"rtdetr_r34vd_6x_coco.yml"
# config_name = f"rtdetr_r18vd_6x_coco.yml"
# run_arg = DetectionInferUtils.init_args()
config_name = config_name if not config_name.endswith(".yml") else config_name[:-4]
# config_file = f"{self.base_dir}/configs/picodet/legacy_model/{config_name}.yml"
if "convnext" in config_name:
model_class = "convnext"
elif "picodet" in config_name:
model_class = "picodet"
elif "ppyoloe" in config_name:
model_class = "ppyoloe"
elif "ssdlite_" in config_name:
model_class = "ssd"
elif "blazeface_" in config_name:
model_class = "face_detection"
elif "yolov6lite_" in config_name:
model_class = "yolov6"
else:
config_name_end_index = FileUtils.get_file_name(config_name).find("_")
model_class = config_name[:config_name_end_index]
config_file = f"{self.detection_config_dir}/{model_class}/{config_name}.yml"
self.run_picodet_coco_model(config_file=config_file)
def run_picodet_coco_batch(self):
"""
批量处理
picodet_l_320_coco_lcnet.yml
:return:
"""
base_dir = f"{self.detection_config_dir}/picodet"
file_name_list = FileUtils.list_dir_or_file(file_dir=base_dir,
add_parent=True,
sort=True,
is_dir=False,
start_with="picodet_",
end_with="_lcnet.yml", )
logger.info(f"total: {len(file_name_list)}")
skip = 7
for index, file_name in enumerate(file_name_list):
if index < skip:
logger.info(f"跳过已经执行的：{index} - {file_name}")
continue
logger.info(f"开始执行：{index} - {file_name}")
self.run_picodet_coco_model(config_file=file_name)
def demo_run_detection_infer():
detection_runner = DetectionRunInfer()
detection_runner.run_picodet_coco()
# detection_runner.run_picodet_coco_batch()
def run_picodet_coco_batch():
"""
批量处理
:return:
"""
# model_class = "picodet"
# model_class = "ppyoloe"
# model_class = "yolox"
# model_class = "yolov3"
# model_class = "yolov5"
# model_class = "yolov6"
# model_class = "yolov7"
# model_class = "rtmdet"
# model_class = "yolov8"
# model_class = "ssd"
model_class = "rtdetr"
with_application = False
# with_application = True
# do_transform = False
do_transform = True
# 需要跳过执行验证的列表
skip_config_name_dict = {
"yolov3": [
"yolov3_darknet53_original_270e_coco.yml",
"yolov3_mobilenet_v1_roadsign.yml"
],
"ssd": [
"ssd_r34_70e_coco.yml",
"ssdlite_ghostnet_320_coco.yml"
]
}
base_dir = f"{Constants.WORK_DIR}/configs/{model_class}"
if with_application:
base_dir = f"{base_dir}/application"
file_name_list = FileUtils.list_dir_or_file(file_dir=base_dir,
add_parent=True,
sort=True,
is_dir=False,
start_with=f"{model_class}",
end_with=".yml", )
logger.info(f"total: {len(file_name_list)}")
skip_config_name_list = skip_config_name_dict.get(model_class, [])
skip = 1
detection_runner = DetectionRunInfer()
for index, file_name in enumerate(file_name_list):
if index < skip:
logger.info(f"跳过已经执行的：{index} - {file_name}")
continue
if f"{FileUtils.get_file_name(file_name)}.yml" in skip_config_name_list:
logger.info(f"跳过无需测试的：{index} - {file_name}")
continue
if "_xpu" in file_name:
continue
if "ppyoloe_crn_m_80e_pcb" in file_name:
continue
logger.info(f"开始执行：{index} - {file_name}")
detection_runner.run_picodet_coco_model(config_file=file_name, do_transform=do_transform)
logger.info(f"完成所有检测: {len(file_name_list)}")
if __name__ == '__main__':
demo_run_detection_infer()
# run_picodet_coco_batch()