def main():
# ---- open the reference image
rgb_img = Image.open('../../../../img/img01.jpg')
n_colors_list = range(1, 21)
testimg_list = []
for i in n_colors_list:
result = median_cut(rgb_img, i)
testimg_list.append(result)
# ---- rescale the reference image into [0,1]
rgb_raster = np.array(rgb_img)
rescale_rgb_raster = rgb_raster / 255.0
# ---- compute 4 IQAs
PSNR_score_list = psnr_list(rescale_rgb_raster, testimg_list)
SSIM_score_list = ssim_list(rescale_rgb_raster, testimg_list)
VIF_score_list = vif_list(rescale_rgb_raster, testimg_list)
GMSD_score_list = gmsd_list(rescale_rgb_raster, testimg_list)
# ----- build the framework and save csv
score_dic = {
"PSNR": PSNR_score_list,
"SSIM": SSIM_score_list,
"VIF": VIF_score_list,
"GMSD": GMSD_score_list
}
score_table = DataFrame(score_dic)
score_table.to_csv('rgb_results/01score_table.csv')
def main():
path_pics = '../../../../img/test_image'
pic_list = open_pics(path_pics)
for pic_nam, pic_path in pic_list:
# ---- open the reference image
rgb_img = Image.open(pic_path)
n_colors_list = range(1, 21)
testimg_list = []
for i in n_colors_list:
result = octree_quantize(rgb_img, i)
testimg_list.append(result)
# ---- rescale the reference image into [0,1]
rgb_raster = np.array(rgb_img)
rescale_rgb_raster = rgb_raster / 255.0
# ---- compute 4 IQAs
PSNR_score_list = psnr_list(rescale_rgb_raster, testimg_list)
SSIM_score_list = ssim_list(rescale_rgb_raster, testimg_list)
VIF_score_list = vif_list(rescale_rgb_raster, testimg_list)
GMSD_score_list = gmsd_list(rescale_rgb_raster, testimg_list)
# ----- build the framework and save csv
score_dic = {
"PSNR": PSNR_score_list,
"SSIM": SSIM_score_list,
"VIF": VIF_score_list,
"GMSD": GMSD_score_list
}
score_table = DataFrame(score_dic)
score_table.to_csv('rgb_results/rgb_50/%02dscore_table.csv' % pic_nam)