| | |
| | | int box_index = index * (classes + 5); |
| | | boxes[index].x = (predictions[box_index + 0] + col + .5) / side * w; |
| | | boxes[index].y = (predictions[box_index + 1] + row + .5) / side * h; |
| | | if(1){ |
| | | if(0){ |
| | | boxes[index].x = (logistic_activate(predictions[box_index + 0]) + col) / side * w; |
| | | boxes[index].y = (logistic_activate(predictions[box_index + 1]) + row) / side * h; |
| | | } |
| | | boxes[index].w = pow(logistic_activate(predictions[box_index + 2]), (square?2:1)) * w; |
| | | boxes[index].h = pow(logistic_activate(predictions[box_index + 3]), (square?2:1)) * h; |
| | | if(1){ |
| | | boxes[index].x = ((col + .5)/side + predictions[box_index + 0] * .5) * w; |
| | | boxes[index].y = ((row + .5)/side + predictions[box_index + 1] * .5) * h; |
| | | boxes[index].w = (exp(predictions[box_index + 2]) * .5) * w; |
| | | boxes[index].h = (exp(predictions[box_index + 3]) * .5) * h; |
| | | } |
| | | for(j = 0; j < classes; ++j){ |
| | | int class_index = index * (classes + 5) + 5; |
| | | float prob = scale*predictions[class_index+j]; |