def __test_img(self, image_path, save_path):
image_raw = ImageHelper.cv2_open_bgr(image_path)
inputs = ImageHelper.bgr2rgb(image_raw)
heatmap_avg = self.__get_heatmap(inputs)
all_peaks = self.__extract_heatmap_info(heatmap_avg)
image_save = self.__draw_key_point(all_peaks, image_raw)
cv2.imwrite(save_path, image_save)
def __test_img(self, image_path, save_path):
Log.info('Image Path: {}'.format(image_path))
image_raw = ImageHelper.cv2_open_bgr(image_path)
inputs = ImageHelper.bgr2rgb(image_raw)
inputs = ImageHelper.resize(inputs, tuple(self.configer.get('data', 'input_size')), Image.CUBIC)
inputs = ToTensor()(inputs)
inputs = Normalize(mean=self.configer.get('trans_params', 'mean'),
std=self.configer.get('trans_params', 'std'))(inputs)
with torch.no_grad():
inputs = inputs.unsqueeze(0).to(self.device)
bbox, cls = self.det_net(inputs)
bbox = bbox.cpu().data.squeeze(0)
cls = F.softmax(cls.cpu().squeeze(0), dim=-1).data
boxes, lbls, scores, has_obj = self.__decode(bbox, cls)
if has_obj:
boxes = boxes.cpu().numpy()
boxes = np.clip(boxes, 0, 1)
lbls = lbls.cpu().numpy()
scores = scores.cpu().numpy()
img_canvas = self.__draw_box(image_raw, boxes, lbls, scores)
else:
# print('None obj detected!')
img_canvas = image_raw
Log.info('Save Path: {}'.format(save_path))
cv2.imwrite(save_path, img_canvas)
# Boxes is within 0-1.
self.__save_json(save_path, boxes, lbls, scores, image_raw)
return image_raw, lbls, scores, boxes, has_obj
def __test_img(self, image_path, save_path):
Log.info('Image Path: {}'.format(image_path))
image_raw = ImageHelper.cv2_open_bgr(image_path)
inputs = ImageHelper.bgr2rgb(image_raw)
paf_avg, heatmap_avg = self.__get_paf_and_heatmap(inputs)
all_peaks = self.__extract_heatmap_info(heatmap_avg)
special_k, connection_all = self.__extract_paf_info(image_raw, paf_avg, all_peaks)
subset, candidate = self.__get_subsets(connection_all, special_k, all_peaks)
subset, img_canvas = self.__draw_key_point(subset, all_peaks, image_raw)
img_canvas = self.__link_key_point(img_canvas, candidate, subset)
cv2.imwrite(save_path, img_canvas)
