fix bug train.py and test.py

model_zoo/official/cv/psenet/default_config.yaml

@@ -55,13 +55,17 @@ TEST_BUFFER_SIZE: 4
 TEST_DROP_REMAINDER: False
 INFERENCE: True
 
-
+# ======================================================================================
 #export options
 device_id: 0
 batch_size: 1
 file_name: "psenet"
 file_format: "MINDIR"
 
+# ======================================================================================
+#postprocess
+result_path: "./scripts/result_Files"
+img_path: ""
 
 ---
 # Help description for each configuration
@@ -80,4 +84,6 @@ batch_size: "batch size"
 file_name: "output file name"
 file_format: "file format choices[AIR, MINDIR, ONNX]"
 object_home: "your direction name"
-modelarts_home: "modelarts working path"
+modelarts_home: "modelarts working path"
+result_path: "result Files path."
+img_path: "image files path."

model_zoo/official/cv/psenet/postprocess.py

@@ -18,19 +18,19 @@ import os
 import math
 import operator
 from functools import reduce
-import argparse
 import numpy as np
 import cv2
-
+from src.model_utils.config import config
-from src.config import config
 from src.ETSNET.pse import pse
 
+
 def sort_to_clockwise(points):
     center = tuple(map(operator.truediv, reduce(lambda x, y: map(operator.add, x, y), points), [len(points)] * 2))
     clockwise_points = sorted(points, key=lambda coord: (-135 - math.degrees(
         math.atan2(*tuple(map(operator.sub, coord, center))[::-1]))) % 360, reverse=True)
     return clockwise_points
 
+
 def write_result_as_txt(image_name, img_bboxes, path):
     if not os.path.isdir(path):
         os.makedirs(path)
@@ -51,10 +51,6 @@ def get_img(image_path):
     image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
     return image
 
-parser = argparse.ArgumentParser(description='postprocess')
-parser.add_argument("--result_path", type=str, default="./scripts/result_Files", help='result Files path.')
-parser.add_argument("--img_path", type=str, default="", help='image files path.')
-args = parser.parse_args()
 
 if __name__ == "__main__":
     if not os.path.isdir('./res/submit_ic15/'):
@@ -62,17 +58,17 @@ if __name__ == "__main__":
     if not os.path.isdir('./res/vis_ic15/'):
         os.makedirs('./res/vis_ic15/')
 
-    file_list = os.listdir(args.img_path)
+    file_list = os.listdir(config.img_path)
     for k in file_list:
         if os.path.splitext(k)[-1].lower() in ['.jpg', '.jpeg', '.png']:
-            img_path = os.path.join(args.img_path, k)
+            img_path = os.path.join(config.img_path, k)
             img = get_img(img_path).reshape(1, 720, 1280, 3)
             img = img[0].astype(np.uint8).copy()
             img_name = os.path.split(img_path)[-1]
 
-            score = np.fromfile(os.path.join(args.result_path, k.split('.')[0] + '_0.bin'), np.float32)
+            score = np.fromfile(os.path.join(config.result_path, k.split('.')[0] + '_0.bin'), np.float32)
             score = score.reshape(1, 1, config.INFER_LONG_SIZE, config.INFER_LONG_SIZE)
-            kernels = np.fromfile(os.path.join(args.result_path, k.split('.')[0] + '_1.bin'), bool)
+            kernels = np.fromfile(os.path.join(config.result_path, k.split('.')[0] + '_1.bin'), bool)
             kernels = kernels.reshape(1, config.KERNEL_NUM, config.INFER_LONG_SIZE, config.INFER_LONG_SIZE)
             score = np.squeeze(score)
             kernels = np.squeeze(kernels)

model_zoo/official/cv/psenet/test.py

@@ -84,7 +84,7 @@ def modelarts_pre_process():
     os.system('cd {}/opencv-3.4.9&&mkdir build&&cd ./build&&{}'.format(local_path, cmake_command))
 
     os.system('cd {}/src/ETSNET/pse&&make clean&&make'.format(local_path))
-    os.system('cd {}&&sed -i ’s/\r//‘ scripts/run_eval_ascend.sh')
+    os.system('cd {}&&sed -i ’s/\r//‘ scripts/run_eval_ascend.sh'.format(local_path))
 
 
 def modelarts_post_process():

model_zoo/official/cv/psenet/train.py

@@ -14,7 +14,8 @@
 # ============================================================================
 
 
-from ast import literal_eval as liter
+import ast
+import operator
 import mindspore.nn as nn
 from mindspore import context
 from mindspore.communication.management import init
@@ -37,6 +38,32 @@ set_seed(1)
 context.set_context(mode=context.GRAPH_MODE, device_target="Ascend", device_id=get_device_id())
 
 
+binOps = {
+    ast.Add: operator.add,
+    ast.Sub: operator.sub,
+    ast.Mult: operator.mul,
+    ast.Div: operator.truediv,
+    ast.Mod: operator.mod
+}
+
+
+def arithmeticeval(s):
+    node = ast.parse(s, mode='eval')
+
+    def _eval(node):
+        if isinstance(node, ast.BinOp):
+            return binOps[type(node.op)](_eval(node.left), _eval(node.right))
+
+        if isinstance(node, ast.Num):
+            return node.n
+
+        if isinstance(node, ast.Expression):
+            return _eval(node.body)
+
+        raise Exception('unsupported type{}'.format(node))
+    return _eval(node.body)
+
+
 def modelarts_pre_process():
     pass
 
@@ -44,8 +71,8 @@ def modelarts_pre_process():
 @moxing_wrapper(pre_process=modelarts_pre_process)
 def train():
     rank_id = 0
-    config.BASE_LR = liter(config.BASE_LR)
+    config.BASE_LR = arithmeticeval(config.BASE_LR)
-    config.WARMUP_RATIO = liter(config.WARMUP_RATIO)
+    config.WARMUP_RATIO = arithmeticeval(config.WARMUP_RATIO)
 
     device_num = get_device_num()
     if config.run_distribute: