simple GAN-generated anime pic detector (thiswaifudoesnotexist.com model v3)

import os
import pandas as pd
from PIL import Image
import time
import sys

def count_and_sort (df, columns):
    g = df.groupby (columns)
    return pd.DataFrame ({"count" : g.size ()}).reset_index ().sort_values ("count", ascending=False).reset_index ()

path = sys.argv[1]
rows = []
sizes = [(400, 400)]
t = time.time ()
columns = ["file", "score", "predicted_category"]

# test for discolorations in smooth areas/background
def diff_score (values, limit):
    total = 0
    count = len (values) - 1
    for i in range (count):
        d = abs (values[i] - values[i + 1])
        if d < limit:
            total = total + d
    return total / count

pos = 0
files = list (filter (lambda f: not f.startswith ("."), os.listdir (path)))
for f in files:
    file = path + "/" + f
    score = 0
    for size in sizes:
        image = Image.open (file).resize (size)
        buf = [image.getdata (), image.rotate (90).getdata ()]
        image.close ()
        pixels = len (buf[0])
        for data in buf:
            r = [pixel[0] for pixel in data]
            g = [pixel[1] for pixel in data]
            b = [pixel[2] for pixel in data]
            r0 = diff_score (r, 2)
            g0 = diff_score (g, 2)
            b0 = diff_score (b, 2)
            score = score + r0 + g0 + b0
    rows.append ({"file"  : f,
                  "score" : score})
    pos = pos + 1
    if pos % 100 == 0:
        print (str (pos) + " images processed")
print (str (time.time () - t) + " seconds elapsed")
df = pd.DataFrame (rows)
print (str (len (df.index)) + " images processed total")
cutoff = 1.1266882918018237
df["predicted_category"] = (df["score"] - cutoff).apply (lambda x: "GAN generated" if x > 0 else "real anime pic")
df[columns].to_csv (sys.argv[2], index=False)