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)