未验证 提交 56ab75b0 编写于 作者: D Double_V 提交者: GitHub

Merge pull request #3116 from LDOUBLEV/test_dyg_whl

delete benchmark utils
......@@ -31,7 +31,7 @@ from ppocr.utils.utility import get_image_file_list, check_and_read_gif
from ppocr.data import create_operators, transform
from ppocr.postprocess import build_post_process
import tools.infer.benchmark_utils as benchmark_utils
# import tools.infer.benchmark_utils as benchmark_utils
logger = get_logger()
......@@ -100,8 +100,6 @@ class TextDetector(object):
self.predictor, self.input_tensor, self.output_tensors, self.config = utility.create_predictor(
args, 'det', logger)
self.det_times = utility.Timer()
def order_points_clockwise(self, pts):
"""
reference from: https://github.com/jrosebr1/imutils/blob/master/imutils/perspective.py
......@@ -158,8 +156,8 @@ class TextDetector(object):
def __call__(self, img):
ori_im = img.copy()
data = {'image': img}
self.det_times.total_time.start()
self.det_times.preprocess_time.start()
st = time.time()
data = transform(data, self.preprocess_op)
img, shape_list = data
if img is None:
......@@ -168,16 +166,12 @@ class TextDetector(object):
shape_list = np.expand_dims(shape_list, axis=0)
img = img.copy()
self.det_times.preprocess_time.end()
self.det_times.inference_time.start()
self.input_tensor.copy_from_cpu(img)
self.predictor.run()
outputs = []
for output_tensor in self.output_tensors:
output = output_tensor.copy_to_cpu()
outputs.append(output)
self.det_times.inference_time.end()
preds = {}
if self.det_algorithm == "EAST":
......@@ -193,8 +187,6 @@ class TextDetector(object):
else:
raise NotImplementedError
self.det_times.postprocess_time.start()
self.predictor.try_shrink_memory()
post_result = self.postprocess_op(preds, shape_list)
dt_boxes = post_result[0]['points']
......@@ -203,10 +195,8 @@ class TextDetector(object):
else:
dt_boxes = self.filter_tag_det_res(dt_boxes, ori_im.shape)
self.det_times.postprocess_time.end()
self.det_times.total_time.end()
self.det_times.img_num += 1
return dt_boxes, self.det_times.total_time.value()
et = time.time()
return dt_boxes, et - st
if __name__ == "__main__":
......@@ -216,7 +206,6 @@ if __name__ == "__main__":
count = 0
total_time = 0
draw_img_save = "./inference_results"
cpu_mem, gpu_mem, gpu_util = 0, 0, 0
# warmup 10 times
fake_img = np.random.uniform(-1, 1, [640, 640, 3]).astype(np.float32)
......@@ -239,12 +228,6 @@ if __name__ == "__main__":
total_time += elapse
count += 1
if args.benchmark:
cm, gm, gu = utility.get_current_memory_mb(0)
cpu_mem += cm
gpu_mem += gm
gpu_util += gu
logger.info("Predict time of {}: {}".format(image_file, elapse))
src_im = utility.draw_text_det_res(dt_boxes, image_file)
img_name_pure = os.path.split(image_file)[-1]
......@@ -252,36 +235,3 @@ if __name__ == "__main__":
"det_res_{}".format(img_name_pure))
logger.info("The visualized image saved in {}".format(img_path))
# print the information about memory and time-spent
if args.benchmark:
mems = {
'cpu_rss_mb': cpu_mem / count,
'gpu_rss_mb': gpu_mem / count,
'gpu_util': gpu_util * 100 / count
}
else:
mems = None
logger.info("The predict time about detection module is as follows: ")
det_time_dict = text_detector.det_times.report(average=True)
det_model_name = args.det_model_dir
if args.benchmark:
# construct log information
model_info = {
'model_name': args.det_model_dir.split('/')[-1],
'precision': args.precision
}
data_info = {
'batch_size': 1,
'shape': 'dynamic_shape',
'data_num': det_time_dict['img_num']
}
perf_info = {
'preprocess_time_s': det_time_dict['preprocess_time'],
'inference_time_s': det_time_dict['inference_time'],
'postprocess_time_s': det_time_dict['postprocess_time'],
'total_time_s': det_time_dict['total_time']
}
benchmark_log = benchmark_utils.PaddleInferBenchmark(
text_detector.config, model_info, data_info, perf_info, mems)
benchmark_log("Det")
Markdown is supported
0% .
You are about to add 0 people to the discussion. Proceed with caution.
先完成此消息的编辑!
想要评论请 注册