def hybrid_forward(self, F, x): x = x.transpose(axes=(0, 2, 1, 3)) x = F.pad(x, mode="constant", pad_width=(0, 0, 0, 0, 0, self.padding, 0, 0), constant_value=0) x = x.transpose(axes=(0, 2, 1, 3)) return x
def get_subwindow_tracking(z, pos_x, pos_y, model_sz, original_sz, avgChans, ctx=mx.cpu()): if original_sz is None: original_sz = model_sz sz = original_sz im_sz = np.shape(z) cen = (sz - 1) / 2 context_xmin = np.floor(pos_x - cen) context_xmax = context_xmin + sz - 1 context_ymin = np.floor(pos_y - cen) context_ymax = context_ymin + sz - 1 left_pad = nd.maximum(0, 1 - context_xmin) top_pad = nd.maximum(0, 1 - context_ymin) right_pad = nd.maximum(0, context_xmax - im_sz[1]) bottom_pad = nd.maximum(0, context_ymax - im_sz[0]) context_xmin = context_xmin + left_pad; context_xmax = context_xmax + left_pad; context_ymin = context_ymin + top_pad; context_ymax = context_ymax + top_pad; paddings = [0, 0, 0, 0, int(top_pad), int(bottom_pad), int(left_pad), int(right_pad)] if avgChans is not None: im_padded_ = z - avgChans im_padded_ = nd.expand_dims(im_padded_, axis = 0) # B H W C im_padded_ = nd.transpose(im_padded_, axes=(0,3,1,2)) # B C H W im_padded_ = nd.pad(im_padded_, pad_width=paddings, mode='constant') im_padded_ = nd.transpose(im_padded_, axes=(0,2,3,1)) # B H W C if avgChans is not None: im_padded_ = im_padded_ + avgChans im_padded = im_padded_[0] im_patch_original = im_padded[int(context_ymin - 1) : int(context_ymax), int(context_xmin - 1) : int(context_xmax), :] if int(model_sz) != int(original_sz): sz_dst_w = np.round(im_patch_original.shape[1] / original_sz * model_sz) sz_dst_h = np.round(im_patch_original.shape[0] / original_sz * model_sz) im_patch = image.fixed_crop(im_patch_original, x0 = 0, y0 = 0, w = im_patch_original.shape[1], h = im_patch_original.shape[0], size = [int(sz_dst_w), int(sz_dst_h)], interp = 1 ) if im_patch.shape[0] != model_sz: im_patch = image.fixed_crop(im_patch_original, x0 = 0, y0 = 0, w = im_patch_original.shape[1], h = im_patch_original.shape[0], size = [int(model_sz), int(model_sz)], interp = 1 ) else: im_patch = im_patch_original return im_patch, im_patch_original
def forward(self, x): return F.pad(x, mode='reflect', pad_width=self.pad_width)
def forward(self, x): return F.pad(x, mode='reflect', pad_width=self.pad_width)
def hybrid_forward(self, F, x): return F.pad(x, mode='reflect', pad_width=self.pad_width)