Update yuv_frame_io.py
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@ -1,33 +1,14 @@
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#!/usr/bin/env python2.7
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import sys
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import getopt
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import math
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import numpy
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# import torch
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# import torch.utils.serialization
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# import PIL
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# import PIL.Image
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import random
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import logging
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import numpy as np
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from scipy.misc import imsave, imresize
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import matplotlib as mpl
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# mpl.use('Agg')
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import matplotlib.pyplot as plt
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# plt.style.use('bmh')
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from skimage.color import rgb2yuv, yuv2rgb
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from PIL import Image
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import os
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from scipy.misc import imread, imsave, imshow, imresize, imsave
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from shutil import copyfile
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from skimage.measure import compare_ssim, compare_psnr
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# from PYTHON_Flow2Color.flowToColor import flowToColor
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# from PYTHON_Flow2Color.writeFlowFile import writeFlowFile
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# from AverageMeter import *
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class YUV_Read():
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def __init__(self, filepath, h, w, format='yuv420', toRGB=True):
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@ -66,33 +47,17 @@ class YUV_Read():
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V = np.reshape(V, [int(self.w / 2), int(self.h / 2)], order='F')
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V = np.transpose(V)
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U = imresize(U, [self.h, self.w], interp='nearest')
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V = imresize(V, [self.h, self.w], interp='nearest')
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U = np.array(Image.fromarray(U).resize([self.w, self.h]))
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V = np.array(Image.fromarray(V).resize([self.w, self.h]))
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# plt.figure(3)
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# plt.title("GT")
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# plt.imshow(np.stack((Y,Y,Y),axis=-1))
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# plt.show()
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#
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# plt.figure(3)
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# plt.title("GT")
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# plt.imshow(np.stack((U,U,U),axis=-1))
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# plt.show()
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# plt.figure(3)
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# plt.title("GT")
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# plt.imshow(np.stack((V,V,V),axis=-1))
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# plt.show()
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if self.toRGB:
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Y = Y / 255.0
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U = U / 255.0 - 0.5
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V = V / 255.0 - 0.5
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self.YUV = np.stack((Y, U, V), axis=-1)
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self.RGB = (255.0 * np.clip(yuv2rgb(self.YUV), 0.0, 1.0)).astype('uint8')
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# plt.figure(3)
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# plt.title("GT")
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# plt.imshow(self.RGB)
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# plt.show()
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self.YUV = None
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return self.RGB, True
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else:
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@ -105,14 +70,10 @@ class YUV_Read():
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class YUV_Write():
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def __init__(self, filepath, fromRGB=True):
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# self.h = h
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# self.w = w
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if os.path.exists(filepath):
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print(filepath)
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# raise("YUV File Exist Error")
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self.fp = open(filepath, 'wb') # no appending
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self.fp = open(filepath, 'wb')
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self.fromRGB = fromRGB
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def write(self, Frame):
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@ -135,9 +96,6 @@ class YUV_Write():
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Y = Y[:, :, 0]
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U = U[:, :, 0]
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V = V[:, :, 0]
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# print(Y.shape)
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# Y = np.transpose(Y,())
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U = np.clip(U + 0.5, 0.0, 1.0)
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V = np.clip(V + 0.5, 0.0, 1.0)
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@ -152,21 +110,6 @@ class YUV_Write():
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U = YUV[::2, ::2, 1]
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V = YUV[::2, ::2, 2]
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# plt.figure(3)
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# plt.title("GT")
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# plt.imshow(np.stack((Y,Y,Y),axis=-1))
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# plt.show()
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#
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# plt.figure(3)
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# plt.title("GT")
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# plt.imshow(np.stack((U,U,U),axis=-1))
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# plt.show()
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# plt.figure(3)
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# plt.title("GT")
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# plt.imshow(np.stack((V,V,V),axis=-1))
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# plt.show()
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# print(Y.shape)
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# print(U.shape)
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Y = Y.flatten() # the first order is 0-dimension so don't need to transpose before flatten
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U = U.flatten()
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V = V.flatten()
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