def _infer_on_img(self, img, ann):
res_detections = detect(self.net,
len(self.train_names),
img.encode('utf-8'),
thresh=self.score_thresh)
res_figures = yolo_preds_to_sly_rects(res_detections,
ann.image_size_wh,
self.train_names)
return res_figures
def inference(self, img):
h, w = img.shape[:2]
cv2.imwrite(self.image_path,
img[:, :, ::-1]) # ok for sequential calls
res_detections = detect(self.net,
len(self.train_names),
self.image_path.encode('utf-8'),
thresh=self.score_thresh)
res_figures = yolo_preds_to_sly_rects(res_detections, (w, h),
self.train_names)
res_ann = sly.Annotation.new_with_objects((w, h), res_figures)
return res_ann
def _raw_detections_to_ann(self, detections_raw, img_size):
labels = common.yolo_preds_to_sly_rects(
detections_raw, self.out_class_mapping, self.confidence_tag_meta)
return sly.Annotation(img_size, labels=labels)