def save_det_result(config_file,
out_dir,
checkpoint_file=None,
img_dir=None,
score_thr=0.2):
"""Visualize results and save to the disk
"""
cfg = Config.fromfile(config_file)
data_test = cfg.data.test
dataset = get_dataset(data_test)
classnames = [dataset.CLASSES]
# use checkpoint path in cfg
if not checkpoint_file:
checkpoint_file = osp.join(cfg.work_dir, 'latest.pth')
# use testset in cfg
if not img_dir:
img_dir = data_test.img_prefix
model = init_detector(config_file, checkpoint_file, device='cuda:0')
img_list = os.listdir(img_dir)
for img_name in img_list:
img_path = osp.join(img_dir, img_name)
img_out_path = osp.join(out_dir, img_name)
result = inference_detector(model, img_path)
img = draw_poly_detections(img_path,
result,
classnames,
scale=1.0,
threshold=score_thr,
colormap=[(212, 188, 0)])
print(img_out_path)
cv2.imwrite(img_out_path, img)
def inference_single_vis(self, srcpath, dstpath, slide_size, chip_size):
detections = self.inference_single(srcpath, slide_size, chip_size)
img = draw_poly_detections(srcpath,
detections,
self.classnames,
scale=1,
threshold=0.3)
cv2.imwrite(dstpath, img)
def inference_single_vis(self, srcpath, dstpath, slide_size, chip_size):
detections = self.inference_single(srcpath, slide_size, chip_size)
#classnames = [cls if cls not in CLASS_MAP else CLASS_MAP[cls] for cls in self.classnames]
classnames = [''] * 15
img = draw_poly_detections(srcpath,
detections,
classnames,
scale=1,
threshold=0.3)
cv2.imwrite(dstpath, img)
def inference_single_vis(self, srcpath, dstpath):
img = mmcv.imread(srcpath)
detections = self.inference_single(img)
img = cv2.resize(img, (512, 512))
print('{}检测到{}个'.format(os.path.basename(srcpath), len(detections)))
print(detections)
# print('detections是什么',len(detections))
img = draw_poly_detections(img,
detections,
self.classnames,
scale=1,
threshold=0.3)
cv2.imwrite(dstpath, img)