(self, img)
| 25 | num_class) |
| 26 | |
| 27 | def predict(self, img): |
| 28 | rows, cols = img.shape[0], img.shape[1] |
| 29 | res_arr = np.zeros((self.max_bbox, 6), dtype=np.float32) |
| 30 | self.yolo.Detect(self.c_point, c_int(rows), c_int(cols), img.ctypes.data_as(POINTER(c_ubyte)), res_arr) |
| 31 | self.bbox_array = res_arr[~(res_arr == 0).all(1)] |
| 32 | return self.bbox_array |
| 33 | |
| 34 | |
| 35 | class_names = [ |
no outgoing calls
no test coverage detected