enhance auto_log

tools/infer/predict_det.py

@@ -31,8 +31,6 @@
 from ppocr.data import create_operators, transform
 from ppocr.postprocess import build_post_process
 
-# import tools.infer.benchmark_utils as benchmark_utils
-
 logger = get_logger()
 
 
@@ -100,6 +98,24 @@ def __init__(self, args):
         self.predictor, self.input_tensor, self.output_tensors, self.config = utility.create_predictor(
             args, 'det', logger)
 
+        if args.benchmark:
+            import auto_log
+            pid = os.getpid()
+            self.autolog = auto_log.AutoLogger(
+                model_name="det",
+                model_precision=args.precision,
+                batch_size=1,
+                data_shape="dynamic",
+                save_path="./output/auto_log.lpg",
+                inference_config=self.config,
+                pids=pid,
+                process_name=None,
+                gpu_ids=0,
+                time_keys=[
+                    'preprocess_time', 'inference_time', 'postprocess_time'
+                ],
+                warmup=10)
+
     def order_points_clockwise(self, pts):
         """
         reference from: https://github.com/jrosebr1/imutils/blob/master/imutils/perspective.py
@@ -158,6 +174,10 @@ def __call__(self, img):
         data = {'image': img}
 
         st = time.time()
+
+        if args.benchmark:
+            self.autolog.times.start()
+
         data = transform(data, self.preprocess_op)
         img, shape_list = data
         if img is None:
@@ -166,12 +186,17 @@ def __call__(self, img):
         shape_list = np.expand_dims(shape_list, axis=0)
         img = img.copy()
 
+        if args.benchmark:
+            self.autolog.times.stamp()
+
         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)
+        if args.benchmark:
+            self.autolog.times.stamp()
 
         preds = {}
         if self.det_algorithm == "EAST":
@@ -195,6 +220,8 @@ def __call__(self, img):
         else:
             dt_boxes = self.filter_tag_det_res(dt_boxes, ori_im.shape)
 
+        if args.benchmark:
+            self.autolog.times.end(stamp=True)
         et = time.time()
         return dt_boxes, et - st
 
@@ -212,8 +239,6 @@ def __call__(self, img):
         for i in range(10):
             res = text_detector(img)
 
-    cpu_mem, gpu_mem, gpu_util = 0, 0, 0
-
     if not os.path.exists(draw_img_save):
         os.makedirs(draw_img_save)
     for image_file in image_file_list:
@@ -237,4 +262,7 @@ def __call__(self, img):
                                 "det_res_{}".format(img_name_pure))
         cv2.imwrite(img_path, src_im)
         logger.info("The visualized image saved in {}".format(img_path))
+
+    if args.benchmark:
+        text_detector.autolog.report()