data_process.py 文件源码

def process_dump_tohdf5data(X,Y, path, phase):

    batch_size = 7000
    X_process = np.zeros((batch_size, 3, patch_h, patch_w), dtype = np.float32)
    Y_process = np.zeros((batch_size, net_density_h, net_density_w), dtype = np.float32)
    with open(os.path.join(path, phase+'.txt'), 'w') as f:
        i1 = 0
        while i1 < len(X):
            if i1+batch_size < len(X):
                i2 = i1 + batch_size
            else:
                i2 = len(X)
            file_name = os.path.join(path, phase+'_'+str(i1)+'.h5')
            with h5py.File(file_name, 'w') as hf:
                for j, img in enumerate(X[i1:i2]):
                    X_process[j] = img.copy().transpose(2,0,1).astype(np.float32)
                    Y_process[j] = density_resize(Y[i1+j], fx = float(net_density_w)/patch_w, fy = float(net_density_h) / patch_h)
                hf['data'] = X_process[:(i2-i1)]
                hf['label'] = Y_process[:(i2-i1)]
            f.write(file_name+'\n')
            i1 += batch_size