diff --git a/README.md b/README.md
index d83fe5f..fd91968 100644
--- a/README.md
+++ b/README.md
@@ -94,6 +94,9 @@ http://127.0.0.1:8080/ocr
+## flask-restful api 内存测试(dbnet)
+200张图片测试稳定在1-1.5G左右的内存
+![](test_imgs/flask-api.png)
## 参考
diff --git a/dbnet/dbnet_infer.py b/dbnet/dbnet_infer.py
index a7c8718..54f9b42 100644
--- a/dbnet/dbnet_infer.py
+++ b/dbnet/dbnet_infer.py
@@ -21,7 +21,7 @@ def draw_bbox(img_path, result, color=(255, 0, 0), thickness=2):
return img_path
-class DBNET(object, metaclass=SingletonType):
+class DBNET(metaclass=SingletonType):
def __init__(self, MODEL_PATH, short_size=640):
self.sess = rt.InferenceSession(MODEL_PATH)
self.short_size = short_size
diff --git a/dbnet/decode.py b/dbnet/decode.py
index d1a9914..925940f 100644
--- a/dbnet/decode.py
+++ b/dbnet/decode.py
@@ -13,7 +13,7 @@ def __init__(self, thresh=0.3, box_thresh=0.5, max_candidates=1000, unclip_ratio
self.unclip_ratio = unclip_ratio
def __call__(self, pred, height, width):
- '''
+ """
batch: (image, polygons, ignore_tags
batch: a dict produced by dataloaders.
image: tensor of shape (N, C, H, W).
@@ -25,7 +25,7 @@ def __call__(self, pred, height, width):
binary: text region segmentation map, with shape (N, H, W)
thresh: [if exists] thresh hold prediction with shape (N, H, W)
thresh_binary: [if exists] binarized with threshhold, (N, H, W)
- '''
+ """
pred = pred[0, :, :]
segmentation = self.binarize(pred)
@@ -38,10 +38,10 @@ def binarize(self, pred):
return pred > self.thresh
def boxes_from_bitmap(self, pred, bitmap, dest_width, dest_height):
- '''
+ """
_bitmap: single map with shape (H, W),
whose values are binarized as {0, 1}
- '''
+ """
assert len(bitmap.shape) == 2
# bitmap = _bitmap.cpu().numpy() # The first channel