(self, model_file, pretrained_file, mean=None,
input_scale=None, raw_scale=None, channel_swap=None,
context_pad=None)
| 33 | R-CNN feature extraction. |
| 34 | """ |
| 35 | def __init__(self, model_file, pretrained_file, mean=None, |
| 36 | input_scale=None, raw_scale=None, channel_swap=None, |
| 37 | context_pad=None): |
| 38 | caffe.Net.__init__(self, model_file, pretrained_file, caffe.TEST) |
| 39 | |
| 40 | # configure pre-processing |
| 41 | in_ = self.inputs[0] |
| 42 | self.transformer = caffe.io.Transformer( |
| 43 | {in_: self.blobs[in_].data.shape}) |
| 44 | self.transformer.set_transpose(in_, (2, 0, 1)) |
| 45 | if mean is not None: |
| 46 | self.transformer.set_mean(in_, mean) |
| 47 | if input_scale is not None: |
| 48 | self.transformer.set_input_scale(in_, input_scale) |
| 49 | if raw_scale is not None: |
| 50 | self.transformer.set_raw_scale(in_, raw_scale) |
| 51 | if channel_swap is not None: |
| 52 | self.transformer.set_channel_swap(in_, channel_swap) |
| 53 | |
| 54 | self.configure_crop(context_pad) |
| 55 | |
| 56 | def detect_windows(self, images_windows): |
| 57 | """ |
nothing calls this directly
no test coverage detected