Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

修复一处拼写错误，一处语法错误 #723

Open
wants to merge 2 commits into
base: master
Choose a base branch
from
Open

修复一处拼写错误，一处语法错误 #723

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
9d73e89
Fix syntax errors
Kakaluoto Mar 7, 2023
6ae8703
fixed some bugs
Kakaluoto Mar 9, 2023
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Jump to
Jump to file
Failed to load files.
Diff view
Diff view
6 changes: 3 additions & 3 deletions pytorch_object_detection/yolov3_spp/build_utils/datasets.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -236,11 +236,11 @@ def __init__(self,
# 放大裁剪目标的宽高
b[2:] = b[2:] * 1.3 + 30 # pad
# 将坐标格式从 x,y,w,h -> xmin,ymin,xmax,ymax
b = xywh2xyxy(b.reshape(-1, 4)).revel().astype(np.int)
b = xywh2xyxy(b.reshape(-1, 4)).ravel().astype(np.int)

# 裁剪bbox坐标到图片内
b[[0, 2]] = np.clip[b[[0, 2]], 0, w]
b[[1, 3]] = np.clip[b[[1, 3]], 0, h]
b[[0, 2]] = np.clip(b[[0, 2]], 0, w)
b[[1, 3]] = np.clip(b[[1, 3]], 0, h)
assert cv2.imwrite(f, img[b[1]:b[3], b[0]:b[2]]), "Failure extracting classifier boxes"
else:
ne += 1 # file empty
Expand Down
4 changes: 2 additions & 2 deletions pytorch_object_detection/yolov3_spp/predict_test.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -20,14 +20,14 @@ def main():
json_path = "./data/pascal_voc_classes.json" # json标签文件
img_path = "test.jpg"
assert os.path.exists(cfg), "cfg file {} dose not exist.".format(cfg)
assert os.path.exists(weights), "weights file {} dose not exist.".format(weights)
assert os.path.exists(weights_path), "weights file {} dose not exist.".format(weights_path)
assert os.path.exists(json_path), "json file {} dose not exist.".format(json_path)
assert os.path.exists(img_path), "image file {} dose not exist.".format(img_path)

with open(json_path, 'r') as f:
class_dict = json.load(f)

category_index = {str(v): str(k) for k, v in class_dict.items()}
category_index = {str(k): str(v) for k, v in class_dict.items()}

input_size = (img_size, img_size)

Expand Down