66     h = cap["height"]
74         y = cap["data"][0:w*h]
75         u = cap["data"][w*h:w*h*5/4]
76         v = cap["data"][w*h*5/4:w*h*6/4]
77         return convert_yuv420_planar_to_rgb_image(y, u, v, w, h)
85         y = cap["data"][0:w*h]
86         return convert_y8_to_rgb_image(y, w, h)
103     h = cap["height"]
104     img = numpy.ndarray(shape=(2*h*w*4,), dtype='<f', buffer=cap["data"])
105     analysis_image = img.reshape(2,h,w,4)
106     mean_image = analysis_image[0,:,:,:].reshape(h,w,4)
107     var_image = analysis_image[1,:,:,:].reshape(h,w,4)
123     w,h = cap["width"], cap["height"]
127     cap["data"] = unpack_raw10_image(cap["data"].reshape(h,w*5/4))
147     h = img.shape[0]
152     msbs = msbs.reshape(h,w)
154     lsbs = img[::, 4::5].reshape(h,w/4)
156             numpy.packbits(numpy.unpackbits(lsbs).reshape(h,w/4,4,2),3), 6)
158     lsbs = lsbs.reshape(h,w/4,4)[:,:,::-1]
159     lsbs = lsbs.reshape(h,w)
161     img16 = numpy.bitwise_or(msbs, lsbs).reshape(h,w)
177     w,h = cap["width"], cap["height"]
181     cap["data"] = unpack_raw12_image(cap["data"].reshape(h,w*3/2))
201     h = img.shape[0]
206     msbs = msbs.reshape(h,w)
208     lsbs = img[::, 2::3].reshape(h,w/2)
210             numpy.packbits(numpy.unpackbits(lsbs).reshape(h,w/2,2,4),3), 4)
212     lsbs = lsbs.reshape(h,w/2,2)[:,:,::-1]
213     lsbs = lsbs.reshape(h,w)
215     img16 = numpy.bitwise_or(msbs, lsbs).reshape(h,w)
247     h = cap["height"]
255         y = cap["data"][0:w*h]
256         u = cap["data"][w*h:w*h*5/4]
257         v = cap["data"][w*h*5/4:w*h*6/4]
258         return ((y.astype(numpy.float32) / 255.0).reshape(h, w, 1),
259                 (u.astype(numpy.float32) / 255.0).reshape(h/2, w/2, 1),
260                 (v.astype(numpy.float32) / 255.0).reshape(h/2, w/2, 1))
262         rgb = decompress_jpeg_to_rgb_image(cap["data"]).reshape(w*h*3)
263         return (rgb[::3].reshape(h,w,1),
264                 rgb[1::3].reshape(h,w,1),
265                 rgb[2::3].reshape(h,w,1))
269         img = numpy.ndarray(shape=(h*w,), dtype='<u2',
270                             buffer=cap["data"][0:w*h*2])
271         img = img.astype(numpy.float32).reshape(h,w) / white_level
291             if w == wfull and h == hfull:
295                 h = hcrop
296             elif w == wcrop and h == hcrop:
302         imgs = [img[::2].reshape(w*h/2)[::2].reshape(h/2,w/2,1),
303                 img[::2].reshape(w*h/2)[1::2].reshape(h/2,w/2,1),
304                 img[1::2].reshape(w*h/2)[::2].reshape(h/2,w/2,1),
305                 img[1::2].reshape(w*h/2)[1::2].reshape(h/2,w/2,1)]
413     h,w = r_plane.shape[:2]
415     img = (((img.reshape(h,w,3) - black_levels) * scale) * gains).clip(0.0,1.0)
416     img = numpy.dot(img.reshape(w*h,3), ccm.T).reshape(h,w,3).clip(0.0,1.0)
445                                        w, h,  argument
465     u = u.reshape(h/2, w/2).repeat(2, axis=1).repeat(2, axis=0)
466     v = v.reshape(h/2, w/2).repeat(2, axis=1).repeat(2, axis=0)
467     yuv = numpy.dstack([y, u.reshape(w*h), v.reshape(w*h)])
468     flt = numpy.empty([h, w, 3], dtype=numpy.float32)
469     flt.reshape(w*h*3)[:] = yuv.reshape(h*w*3)[:]
470     flt = numpy.dot(flt.reshape(w*h,3), ccm_yuv_to_rgb.T).clip(0, 255)
471     rgb = numpy.empty([h, w, 3], dtype=numpy.uint8)
472     rgb.reshape(w*h*3)[:] = flt.reshape(w*h*3)[:]
475 def convert_y8_to_rgb_image(y_plane, w, h):  argument
487     rgb = numpy.empty([h, w, 3], dtype=numpy.uint8)
488     rgb.reshape(w*h*3)[:] = y3.reshape(w*h*3)[:]
502     h = img.size[1]
506         return a.reshape(h,w,3) / 255.0
509         return a.reshape(h*w).repeat(3).reshape(h,w,3) / 255.0
515                              w, h,  argument
539             y = numpy.fromfile(f, numpy.uint8, w*h, "")
540             v = numpy.fromfile(f, numpy.uint8, w*h/4, "")
541             u = numpy.fromfile(f, numpy.uint8, w*h/4, "")
544             y = numpy.fromfile(f, numpy.uint8, w*h, "")
545             vu = numpy.fromfile(f, numpy.uint8, w*h/2, "")
551                 y,u,v,w,h,ccm_yuv_to_rgb,yuv_off)
554 def load_yuv420_planar_to_yuv_planes(yuv_fname, w, h):  argument
569         y = numpy.fromfile(f, numpy.uint8, w*h, "")
570         v = numpy.fromfile(f, numpy.uint8, w*h/4, "")
571         u = numpy.fromfile(f, numpy.uint8, w*h/4, "")
572         return ((y.astype(numpy.float32) / 255.0).reshape(h, w, 1),
573                 (u.astype(numpy.float32) / 255.0).reshape(h/2, w/2, 1),
574                 (v.astype(numpy.float32) / 255.0).reshape(h/2, w/2, 1))
588     h = img.size[1]
589     return numpy.array(img).reshape(h,w,3) / 255.0
643     h = img.shape[0]
645     img2 = numpy.empty([h, w, 3], dtype=numpy.float32)
646     img2.reshape(w*h*3)[:] = (numpy.dot(img.reshape(h*w, 3), mat.T)
647                              ).reshape(w*h*3)[:]
756     (h, w, chans) = img.shape
760         img3 = (img * 255.0).astype(numpy.uint8).repeat(3).reshape(h,w,3)
784     h,w,chans = img.shape
787     h = (h/f)*f
789     img = img[0:h:,0:w:,::]
792         ch = img.reshape(h*w*chans)[i::chans].reshape(h,w)
793         ch = ch.reshape(h,w/f,f).mean(2).reshape(h,w/f)
794         ch = ch.T.reshape(w/f,h/f,f).mean(2).T.reshape(h/f,w/f)
795         chs.append(ch.reshape(h*w/(f*f)))
796     img = numpy.vstack(chs).T.reshape(h/f,w/f,chans)