def clipped_zoom(img, zoom_factor):
# img : numpy.ndarray
h, w, _ = img.shape
# ceil crop height(= crop width)
ch = int(np.ceil(h / zoom_factor))
cw = int(np.ceil(w / zoom_factor))
top = (h - ch) // 2
left = (w - cw) // 2
img = scizoom(img[top:top + ch, left:left + cw],
(zoom_factor, zoom_factor, 1),
order=1)
# trim off any extra pixels
trim_top = (img.shape[0] - h) // 2
trim_left = (img.shape[1] - w) // 2
# trim_top = (h - img.shape[0]) // 2
# trim_left = (w - img.shape[1]) // 2
if trim_top < 0 or trim_left < 0:
# print 'h, w, zoom_factor, ch, cw, image.shape :', h, w, zoom_factor, ch, cw, img.shape
# raise NotImplemented
img = (np.clip(img, 0, 1) * 255).astype(np.uint8)
img = PILImage.fromarray(img.squeeze(), mode='L')
img = img.resize((w, h), PILImage.BOX)
img = np.array(img, dtype=np.float32) / 255.
trim_top = 0
trim_left = 0
img = img[trim_top:trim_top + h, trim_left:trim_left + w]
return img
def clipped_zoom(img, zoom_factor):
h = img.shape[0]
# ceil crop height(= crop width)
ch = int(np.ceil(h / zoom_factor))
top = (h - ch) // 2
img = scizoom(img[top:top + ch, top:top + ch], (zoom_factor, zoom_factor, 1), order=1)
# trim off any extra pixels
trim_top = (img.shape[0] - h) // 2
return img[trim_top:trim_top + h, trim_top:trim_top + h]
def clipped_zoom(img, zoom_factor):
# clipping along the width dimension:
ch0 = int(np.ceil(img.shape[0] / float(zoom_factor)))
top0 = (img.shape[0] - ch0) // 2
# clipping along the height dimension:
ch1 = int(np.ceil(img.shape[1] / float(zoom_factor)))
top1 = (img.shape[1] - ch1) // 2
img = scizoom(img[top0:top0 + ch0, top1:top1 + ch1],
(zoom_factor, zoom_factor, 1),
order=1)
return img
def clipped_zoom(img, zoom_factor):
h, w = img.shape[:2]
# ceil crop height(= crop width)
ch_h = int(np.ceil(h / float(zoom_factor)))
ch_w = int(np.ceil(w / float(zoom_factor)))
top = (h - ch_h) // 2
left = (w - ch_w) // 2
img = scizoom(img[top:top + ch_h, left:left + ch_w],
(zoom_factor, zoom_factor, 1),
order=1)
# trim off any extra pixels
trim_top = (img.shape[0] - h) // 2
trim_left = (img.shape[1] - w) // 2
return img[trim_top:trim_top + h, trim_left:trim_left + w]
def clipped_zoom(img, zoom_factor):
h = img.shape[0]
w = img.shape[1]
# ceil crop height(= crop width)
ch = int(np.ceil(h / float(zoom_factor)))
cw = int(np.ceil(w / float(zoom_factor)))
top = (h - ch) // 2
side = (w - cw) // 2
img = scizoom(img[top:top + ch, side:side + cw],
(zoom_factor, zoom_factor, 1), order=1)
# trim off any extra pixels
trim_top = (img.shape[0] - h) // 2
trim_side = (img.shape[1] - w) // 2
return img[trim_top:trim_top + h, trim_side:trim_side + w]
def clipped_zoom(img, zoom_factor):
h = img.shape[0]
w = img.shape[1]
# ceil crop height(= crop width)
ch = int(np.ceil(h / zoom_factor))
cw = int(np.ceil(w / zoom_factor))
top_h = (h - ch) // 2
top_w = (w - cw) // 2
img = scizoom(img[top_h:top_h + ch, top_w:top_w + cw],
(zoom_factor, zoom_factor, 1),
order=1)
# trim off any extra pixels
trim_top_h = (img.shape[0] - h) // 2
trim_top_w = (img.shape[1] - w) // 2
return img[trim_top_h:trim_top_h + h, trim_top_w:trim_top_w + w]
