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Fix undefined variables in imresizemex function #9

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Fix undefined variables in imresizemex function #9

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25 changes: 9 additions & 16 deletions mindediting/dataset/src/vimeo_preprocess.py
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Original file line number Diff line number Diff line change
Expand Up @@ -58,28 +58,21 @@ def imresizemex(inimg, weights, indices, dim):
out_shape[dim] = w_shape[0]
outimg = np.zeros(out_shape)
if dim == 0:
index = 1
slice_start, slice_end = indice, i_img
outimg_start, outimg_end = i_w, i_img
for i_img in range(in_shape[1]):
for i_w in range(w_shape[0]):
w = weights[i_w, :]
indice = indices[i_w, :]
im_slice = inimg[indice, i_img].astype(np.float64)
ind = indices[i_w, :]
im_slice = inimg[ind, i_img].astype(np.float64)
mult = np.multiply(np.squeeze(im_slice, axis=0), w.T)
outimg[i_w, i_img] = np.sum(mult, axis=0)
elif dim == 1:
index = 0
slice_start, slice_end = i_img, indice
outimg_start, outimg_end = i_img, i_w

for i_img in range(in_shape[index]):
for i_w in range(w_shape[0]):
w = weights[i_w, :]
indice = indices[i_w, :]
im_slice = inimg[slice_start, slice_end].astype(np.float64)
mult = np.multiply(np.squeeze(im_slice, axis=0), w.T)
outimg[outimg_start, outimg_end] = np.sum(mult, axis=0)
for i_img in range(in_shape[0]):
for i_w in range(w_shape[0]):
w = weights[i_w, :]
ind = indices[i_w, :]
im_slice = inimg[i_img, ind].astype(np.float64)
mult = np.multiply(np.squeeze(im_slice, axis=0), w.T)
outimg[i_img, i_w] = np.sum(mult, axis=0)

if inimg.dtype == np.uint8:
outimg = np.clip(outimg, 0, 255)
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25 changes: 9 additions & 16 deletions mindediting/deploy/data_io/srdiff_sr/utils_preprocess.py
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Original file line number Diff line number Diff line change
Expand Up @@ -53,28 +53,21 @@ def imresizemex(inimg, weights, indices, dim):
out_shape[dim] = w_shape[0]
outimg = np.zeros(out_shape)
if dim == 0:
index = 1
slice_start, slice_end = indice, i_img
outimg_start, outimg_end = i_w, i_img
for i_img in range(in_shape[1]):
for i_w in range(w_shape[0]):
w = weights[i_w, :]
indice = indices[i_w, :]
im_slice = inimg[indice, i_img].astype(np.float64)
ind = indices[i_w, :]
im_slice = inimg[ind, i_img].astype(np.float64)
mult = np.multiply(np.squeeze(im_slice, axis=0), w.T)
outimg[i_w, i_img] = np.sum(mult, axis=0)
elif dim == 1:
index = 0
slice_start, slice_end = i_img, indice
outimg_start, outimg_end = i_img, i_w

for i_img in range(in_shape[index]):
for i_w in range(w_shape[0]):
w = weights[i_w, :]
indice = indices[i_w, :]
im_slice = inimg[slice_start, slice_end].astype(np.float64)
mult = np.multiply(np.squeeze(im_slice, axis=0), w.T)
outimg[outimg_start, outimg_end] = np.sum(mult, axis=0)
for i_img in range(in_shape[0]):
for i_w in range(w_shape[0]):
w = weights[i_w, :]
ind = indices[i_w, :]
im_slice = inimg[i_img, ind].astype(np.float64)
mult = np.multiply(np.squeeze(im_slice, axis=0), w.T)
outimg[i_img, i_w] = np.sum(mult, axis=0)

if inimg.dtype == np.uint8:
outimg = np.clip(outimg, 0, 255)
Expand Down