67 lines
2.4 KiB
Python
67 lines
2.4 KiB
Python
import PIL.Image # 安装依赖包：pip3 install pillow
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from math import log
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from SSIM_PIL import compare_ssim # 安装依赖包：pip3 install SSIM-PIL
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def get_ssim_at_quality(photo, quality):
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"""Return the ssim for this JPEG image saved at the specified quality"""
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ssim_photo = "tmp.jpg"
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# optimize is omitted here as it doesn't affect
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# quality but requires additional memory and cpu
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photo.save(ssim_photo, format="JPEG", quality=quality, progressive=True)
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ssim_score = compare_ssim(photo, PIL.Image.open(ssim_photo))
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return ssim_score
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def _ssim_iteration_count(lo, hi):
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"""Return the depth of the binary search tree for this range"""
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if lo >= hi:
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return 0
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else:
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return int(log(hi - lo, 2)) + 1
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def jpeg_dynamic_quality(original_photo):
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"""Return an integer representing the quality that this JPEG image should be
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saved at to attain the quality threshold specified for this photo class.
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Args:
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original_photo - a prepared PIL JPEG image (only JPEG is supported)
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"""
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ssim_goal = 0.9 #the original value is 0.95
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hi = 35 #the original value is 85
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lo = 30 #the original value is 80
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# working on a smaller size image doesn't give worse results but is faster
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# changing this value requires updating the calculated thresholds
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photo = original_photo.resize((200, 200))
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# if not _should_use_dynamic_quality():
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# default_ssim = get_ssim_at_quality(photo, hi)
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# return hi, default_ssim
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# 95 is the highest useful value for JPEG. Higher values cause different behavior
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# Used to establish the image's intrinsic ssim without encoder artifacts
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normalized_ssim = get_ssim_at_quality(photo, 10)
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selected_quality = selected_ssim = None
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# loop bisection. ssim function increases monotonically so this will converge
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for i in range(_ssim_iteration_count(lo, hi)):
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curr_quality = (lo + hi) // 2
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curr_ssim = get_ssim_at_quality(photo, curr_quality)
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ssim_ratio = curr_ssim / normalized_ssim
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if ssim_ratio >= ssim_goal:
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# continue to check whether a lower quality level also exceeds the goal
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selected_quality = curr_quality
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selected_ssim = curr_ssim
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hi = curr_quality
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else:
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lo = curr_quality
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if selected_quality:
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return selected_quality, selected_ssim
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else:
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default_ssim = get_ssim_at_quality(photo, hi)
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return hi, default_ssim
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