# check evaluated number of images # check score in list, score 0, 0.5, 1 # check total score_alignment, score_quality import csv import os import ast csv_file = 'your_file.csv' folder_path = 'your_folder' def check(csv_file, image_folder, s1, s2, s3, s4, s5): print(f"###################{csv_file}#######################") # 1. Count CSV rows (excluding header) with open(csv_file, newline='') as f: reader = list(csv.DictReader(f)) num_rows = len(reader) # 2. Count files in folder num_files = len([name for name in os.listdir(image_folder) if name.endswith('.png') or name.endswith('.jpg')]) print(f"CSV rows: {num_rows}, Files in folder: {num_files}") if num_rows != num_files: print("Row and image count do not match!") else: print("Row and image count match.") # 3. Check 's1', 's2', 's3' columns and calculate averages valid_values = {0, 0.5, 1} s1_averages, s2_averages, s3_averages = [], [], [] invalid_rows = [] s4_values, s5_values = [], [] invalid_s4_s5_rows = [] for idx, row in enumerate(reader): valid_row = True row_avgs = [] for col in [s1, s2, s3]: vals = ast.literal_eval(row[col]) # Parse the list if not isinstance(vals, list): # raise ValueError # not list valid_row = False if not all(v in valid_values for v in vals): valid_row = False # not 0, 0.5, or 1 else: avg = sum(vals) / len(vals) if vals else 0 row_avgs.append(avg) if not valid_row: invalid_rows.append(idx+2) # +2 for header and 0-indexing if valid_row: s1_averages.append(row_avgs[0]) s2_averages.append(row_avgs[1]) s3_averages.append(row_avgs[2]) # Check s4 and s5 s4_ok = float(row[s4])<=1.0 and float(row[s4])>=0.0 s5_ok = float(row[s5])<=1.0 and float(row[s5])>=0.0 if s4_ok and s5_ok: s4_values.append(float(row[s4])) s5_values.append(float(row[s5])) else: invalid_s4_s5_rows.append(idx+2) print(type(float(row[s4]))) if invalid_rows: print(f"Invalid rows in 's1', 's2', or 's3': {invalid_rows}") else: print("All rows in 's1', 's2', and 's3' are valid.") if invalid_s4_s5_rows: print(f"Invalid rows in 's4' or 's5': {invalid_s4_s5_rows}") else: print("All rows in 's4' and 's5' are valid.") overall_s1_avg = sum(s1_averages) / len(s1_averages) if s1_averages else 0 overall_s2_avg = sum(s2_averages) / len(s2_averages) if s2_averages else 0 overall_s3_avg = sum(s3_averages) / len(s3_averages) if s3_averages else 0 # print(f"Average for s1: {overall_s1_avg:.3f}") # print(f"Average for s2: {overall_s2_avg:.3f}") # print(f"Average for s3: {overall_s3_avg:.3f}") overall_s4_avg = sum(s4_values) / len(s4_values) if s4_values else 0 overall_s5_avg = sum(s5_values) / len(s5_values) if s5_values else 0 # print(f"Average for s4: {overall_s4_avg:.3f}") # print(f"Average for s5: {overall_s5_avg:.3f}") return overall_s1_avg, overall_s2_avg, overall_s3_avg, overall_s4_avg, overall_s5_avg def check2(csv_file, image_folder, s1, s2, s3, s4, s5, s6): print(f"###################{csv_file}#######################") # 1. Count CSV rows (excluding header) with open(csv_file, newline='') as f: reader = list(csv.DictReader(f)) num_rows = len(reader) # 2. Count files in folder num_files = len([name for name in os.listdir(image_folder) if name.endswith('.png') or name.endswith('.jpg')]) print(f"CSV rows: {num_rows}, Files in folder: {num_files}") if num_rows != num_files: print("Row and image count do not match!") else: print("Row and image count match.") # 3. Check 's1', 's2', 's3' columns and calculate averages valid_values = {0, 0.5, 1} s1_averages, s2_averages, s3_averages = [], [], [] invalid_rows = [] s4_values, s5_values, s6_values = [], [], [] invalid_s4_s5_s6_rows = [] s45_values = [] w1 = 0.7 w2 = 0.3 for idx, row in enumerate(reader): valid_row = True row_avgs = [] for col in [s1, s2, s3]: vals = ast.literal_eval(row[col]) # Parse the list if not isinstance(vals, list): # raise ValueError # not list valid_row = False if not all(v in valid_values for v in vals): valid_row = False # not 0, 0.5, or 1 print(vals) print("HHHHHHH2") else: avg = sum(vals) / len(vals) if vals else 0 row_avgs.append(avg) if not valid_row: invalid_rows.append(idx+2) # +2 for header and 0-indexing if valid_row: s1_averages.append(row_avgs[0]) s2_averages.append(row_avgs[1]) s3_averages.append(row_avgs[2]) # Check s4 and s5 s4_ok = float(row[s4])<=1.0 and float(row[s4])>=0.0 s5_ok = float(row[s5])<=1.0 and float(row[s5])>=0.0 s6_ok = float(row[s6])<=1.0 and float(row[s6])>=0.0 if s4_ok and s5_ok and s6_ok: s4_values.append(float(row[s4])) s5_values.append(float(row[s5])) s6_values.append(float(row[s6])) s45_values.append((w1*float(row[s4]) + w2*float(row[s5]))) else: invalid_s4_s5_s6_rows.append(idx+2) print(type(float(row[s4]))) if invalid_rows: print(f"Invalid rows in 's1', 's2', or 's3': {invalid_rows}") else: print("All rows in 's1', 's2', and 's3' are valid.") if invalid_s4_s5_s6_rows: print(f"Invalid rows in 's4' or 's5': {invalid_s4_s5_s6_rows}") else: print("All rows in 's4' and 's5' are valid.") overall_s1_avg = sum(s1_averages) / len(s1_averages) if s1_averages else 0 overall_s2_avg = sum(s2_averages) / len(s2_averages) if s2_averages else 0 overall_s3_avg = sum(s3_averages) / len(s3_averages) if s3_averages else 0 # print(f"Average for s1: {overall_s1_avg:.3f}") # print(f"Average for s2: {overall_s2_avg:.3f}") # print(f"Average for s3: {overall_s3_avg:.3f}") overall_s4_avg = sum(s4_values) / len(s4_values) if s4_values else 0 overall_s5_avg = sum(s5_values) / len(s5_values) if s5_values else 0 overall_s6_avg = sum(s6_values) / len(s6_values) if s6_values else 0 overall_s45_avg = sum(s45_values) / len(s45_values) if s45_values else 0 # print(f"Average for s4: {overall_s4_avg:.3f}") # print(f"Average for s5: {overall_s5_avg:.3f}") # print(f"Average for s6: {overall_s6_avg:.3f}") # print(f"Average for s45: {overall_s45_avg:.3f}") return overall_s1_avg, overall_s2_avg, overall_s3_avg, overall_s4_avg, overall_s5_avg, overall_s6_avg,overall_s45_avg if __name__ == "__main__": # model_names = [ # "flux1-schnell", # "sd35_large", # "sd35_medium", # "sd30_medium", # "flux1-dev", # "playground-v25", # "hidream", # "janus_pro_7B", # "show-o-512", # "bagel", # "emu3", # "GoT", # "Gemini", # "GPT", # ] model_names = [ "hidream", "flux1-dev", "flux1-schnell", "playground-v25", "sd30_medium", "sd35_medium", "sd35_large", "qwen_image", "bagel", "emu3", "janus_pro_7B", "show-o-512", "GoT", "Gemini", "GPT", "nano_banana", ] s4_list = [] s5_list = [] s6_list = [] s45_list = [] for model_name in model_names: # csv_path = f'/group/xihuiliu/sky/reasoning/csv/idiom/{model_name}.csv' # image_folder = f'/group/xihuiliu/sky/reasoning/images/idiom/{model_name}' # csv_path = f'/group/xihuiliu/sky/reasoning/csv/idiom/{model_name}_4o-pipeline.csv' # image_folder = f'/group/xihuiliu/sky/reasoning/models/GPT4o_pipeline/images_4o-pipeline/{model_name}' # csv_path = f'/group/xihuiliu/sky/reasoning/csv/text_image_new/{model_name}.csv' # image_folder = f'/group/xihuiliu/sky/reasoning/images/text_image_new/{model_name}' # csv_path = f'/group/xihuiliu/sky/reasoning/csv/text_image_new/{model_name}_4o-pipeline.csv' # image_folder = f'/group/xihuiliu/sky/reasoning/models/GPT4o_pipeline/images_text_image_4o-pipeline/{model_name}' # s1_column = 'score_alignment' # s2_column = 'score_quality' # s3_column = 'score_quality' # s4_column = 'score_a_avg' # s5_column = 'score_q_avg' # s1,s2,s3,s4,s5=check(csv_path, image_folder, s1_column, s2_column, s3_column, s4_column, s5_column) # score = (0.9*s4+0.1*s5)*100 # s4_list.append(score) # # s5_list.append(s5*100) # csv_path = f'/group/xihuiliu/sky/reasoning/csv/entity/{model_name}_4o-pipeline.csv' # image_folder = f'/group/xihuiliu/sky/reasoning/models/GPT4o_pipeline/images_entity_4o-pipeline/{model_name}' # csv_path = f'/group/xihuiliu/sky/reasoning/csv/entity/{model_name}.csv' # image_folder = f'/group/xihuiliu/sky/reasoning/images/common_sense/{model_name}' # s1_column = 'score_entity' # s2_column = 'score_detail' # s3_column = 'score_quality' # s4_column = 'score_e_avg' # s5_column = 'score_d_avg' # s6_column = 'score_q_avg' csv_path = f'/group/xihuiliu/sky/reasoning/csv/physics/{model_name}_4o-pipeline.csv' image_folder = f'/group/xihuiliu/sky/reasoning/models/GPT4o_pipeline/images_physics_4o-pipeline/{model_name}' # csv_path = f'/group/xihuiliu/sky/reasoning/csv/physics/{model_name}.csv' # image_folder = f'/group/xihuiliu/sky/reasoning/images/physics/{model_name}' s1_column = 'score_scientific' s2_column = 'score_detail' s3_column = 'score_quality' s4_column = 'score_s_avg' s5_column = 'score_d_avg' s6_column = 'score_q_avg' s1,s2,s3,s4,s5,s6,s45=check2(csv_path, image_folder, s1_column, s2_column, s3_column, s4_column, s5_column, s6_column) s4_list.append(s4*100) s5_list.append(s5*100) s6_list.append(s6*100) score = (0.7*s4+0.2*s5+0.1*s6)*100 s45_list.append(score) for i, model_name in enumerate(model_names): # print(round(s4_list[i],1)) # print(f"{model_name},", round(s4_list[i],1), ",", round(s5_list[i],1), ",", round(s6_list[i],1)) # print(f"{model_name},", round(s45_list[i],1), ",", round(s6_list[i],1)) print(round(s45_list[i],1)) # idiom: GPT 198 # hidream, 48.5 , 87.2 # flux1-dev, 39.1 , 83.4 # flux1-schnell, 40.9 , 83.1 # playground-v25, 43.9 , 87.8 # sd30_medium, 35.9 , 81.4 # sd35_medium, 34.4 , 80.6 # sd35_large, 35.6 , 85.3 # emu3, 33.1 , 82.9 # janus_pro_7B, 25.5 , 78.0 # show-o-512, 33.1 , 82.5 # GoT, 29.7 , 76.4 # bagel, 44.6 , 84.3 # Gemini, 52.4 , 87.8 # 从133开始错误： GPT, 75.6 , 95.4, 更新：GPT, 75.7 , 94.5 # qwen_image, 51.7 , 89.7 #idiom pipeline # hidream, 64.4 , 91.9 # flux1-dev, 66.2 , 90.5 # flux1-schnell, 68.2 , 87.4 # playground-v25, 55.8 , 88.7 # sd30_medium, 65.7 , 87.6 # sd35_medium, 66.8 , 88.5 # sd35_large, 67.7 , 90.4 # emu3, 56.0 , 84.2 # janus_pro_7B, 63.1 , 82.9 # show-o-512, 64.2 , 89.5 # GoT, 51.8 , 81.4 # bagel, 67.7 , 87.8 # Gemini, 67.1 , 91.5 # GPT, 77.3 , 93.8 # entity pipeline # hidream, 76.4 , 77.9 , 96.8 # 有错误：flux1-dev, 70.6 , 77.2 , 95.9 更新后：flux1-dev, 69.9 , 76.9 , 96.1 # flux1-schnell, 70.1 , 78.4 , 94.9 # playground-v25, 71.5 , 68.9 , 94.7 # sd30_medium, 71.8 , 76.9 , 96.1 # sd35_medium, 70.1 , 77.2 , 95.9 # sd35_large, 76.8 , 79.8 , 95.6 # emu3, 60.8 , 67.8 , 90.6 # janus_pro_7B, 67.3 , 74.3 , 93.0 # show-o-512, 64.6 , 70.9 , 94.0 # GoT, 48.7 , 57.9 , 89.2 # bagel, 66.9 , 76.8 , 94.7 # Gemini, 77.9 , 77.8 , 96.1 # GPT, 82.6 , 85.4 , 98.0 #整体 # hidream, 76.4 , 77.9 , 96.8 # flux1-dev, 69.9 , 76.9 , 96.1 # flux1-schnell, 70.1 , 78.4 , 94.9 # playground-v25, 71.5 , 68.9 , 94.7 # sd30_medium, 71.8 , 76.9 , 96.1 # sd35_medium, 70.1 , 77.2 , 95.9 # sd35_large, 76.8 , 79.8 , 95.6 # emu3, 60.8 , 67.8 , 90.6 # janus_pro_7B, 67.3 , 74.3 , 93.0 # show-o-512, 64.6 , 70.9 , 94.0 # GoT, 48.7 , 57.9 , 89.2 # bagel, 66.9 , 76.8 , 94.7 # Gemini, 77.9 , 77.8 , 96.1 # GPT, 82.6 , 85.4 , 98.0 #!!!整体 0.7 0.3 # hidream, 76.9 , 96.8 # flux1-dev, 72.0 , 96.1 # flux1-schnell, 72.6 , 94.9 # playground-v25, 70.7 , 94.7 # sd30_medium, 73.3 , 96.1 # sd35_medium, 72.2 , 95.9 # sd35_large, 77.7 , 95.6 # emu3, 62.9 , 90.6 # janus_pro_7B, 69.4 , 93.0 # show-o-512, 66.5 , 94.0 # GoT, 51.5 , 89.2 # bagel, 69.9 , 94.7 # Gemini, 77.9 , 96.1 # GPT, 83.4 , 98.0 # entity # hidream, 47.1 , 70.4 , 94.1 # 有错误：flux1-dev, 40.7 , 59.8 , 90.1 更新后：flux1-dev, 39.2 , 58.7 , 90.6 # flux1-schnell, 37.5 , 62.0 , 91.5 # playground-v25, 43.0 , 60.9 , 92.4 # sd30_medium, 36.5 , 56.3 , 90.1 # sd35_medium, 37.9 , 60.8 , 92.1 # sd35_large, 40.7 , 60.4 , 92.6 # emu3, 26.1 , 51.8 , 85.2 # janus_pro_7B, 31.4 , 55.1 , 87.6 # 有错误,一个是null show-o-512, 28.2 , 50.5 , 87.4 # GoT, 25.8 , 43.1 , 86.2 # bagel, 47.9 , 63.0 , 91.6 # 从49开始错误： Gemini, 14.2 , 21.9 , 70.4 更新后：Gemini, 66.0 , 69.3 , 94.3 # 从54开始错误： GPT, 19.2 , 24.3 , 70.1 更新后：GPT, 76.2 , 80.3 , 96.6 #整体 # hidream, 47.1 , 70.4 , 94.1 # flux1-dev, 39.2 , 58.7 , 90.6 # flux1-schnell, 37.5 , 62.0 , 91.5 # playground-v25, 43.0 , 60.9 , 92.4 # sd30_medium, 36.5 , 56.3 , 90.1 # sd35_medium, 37.9 , 60.8 , 92.1 # sd35_large, 40.7 , 60.4 , 92.6 # emu3, 26.1 , 51.8 , 85.2 # janus_pro_7B, 31.4 , 55.1 , 87.6 # show-o-512, 28.2 , 50.5 , 87.4 # GoT, 25.8 , 43.1 , 86.2 # bagel, 47.9 , 63.0 , 91.6 # Gemini, 66.0 , 69.3 , 94.3 # GPT, 76.2 , 80.3 , 96.6 #整体 0.7 0.3 # hidream, 54.1 , 94.1 # flux1-dev, 45.1 , 90.6 # flux1-schnell, 44.8 , 91.5 # playground-v25, 48.4 , 92.4 # sd30_medium, 42.4 , 90.1 # sd35_medium, 44.8 , 92.1 # sd35_large, 46.6 , 92.6 # emu3, 33.8 , 85.2 # janus_pro_7B, 38.5 , 87.6 # show-o-512, 34.9 , 87.4 # GoT, 31.0 , 86.2 # bagel, 52.4 , 91.6 # Gemini, 67.0 , 94.3 # GPT, 77.5 , 96.6 # qwen_image, 60.6 , 96.2 # text-image # hidream, 72.3 , 85.5 # flux1-dev, 56.9 , 76.5 # flux1-schnell, 65.1 , 74.5 # 有错误,一个是null：playground-v25, 38.5 , 72.1 # sd30_medium, 60.9 , 71.3 # sd35_medium, 58.0 , 70.1 # sd35_large, 62.2 , 75.4 # 有错误,一个是null：emu3, 33.7 , 68.7 # janus_pro_7B, 37.2 , 70.9 # show-o-512, 35.3 , 80.3 # 从3开始错误：GoT, 7.2 , 56.9, 更新后： GoT, 30.6 , 70.7 # bagel, 44.0 , 73.7 # 从53开始错误：Gemini, 28.0 , 70.1 更新后：Gemini, 73.0 , 83.3 # GPT, 86.9 , 97.6 # qwen_image, 72.0 , 81.3 # text-image pipeline # hidream, 77.5 , 87.0 # flux1-dev, 69.8 , 80.5 # flux1-schnell, 71.6 , 78.7 # playground-v25, 40.5 , 76.5 # sd30_medium, 70.9 , 83.1 # sd35_medium, 69.2 , 79.9 # sd35_large, 72.4 , 84.4 # emu3, 41.5 , 74.7 # janus_pro_7B, 54.9 , 80.5 # show-o-512, 42.9 , 83.5 # 从177开始错误: GoT, 36.4 , 73.1 更新后：GoT, 36.4 , 73.1 # 有错误：bagel, 61.0 , 79.1 更新后： bagel, 61.5 , 79.7 # 从20开始错误: Gemini, 20.7 , 74.9 更新后： Gemini, 78.4 , 89.4 # 从85开始错误: GPT, 41.7 , 86.1 更新后： GPT, 83.0 , 97.5 #scientific # hidream, 45.0 , 72.5 # 有错误: flux1-dev, 38.8 , 64.9 更新：flux1-dev, 38.8 , 65.1 , 80.9 # flux1-schnell, 41.2 , 73.0 # 有错误: playground-v25, 42.8 , 67.2, 更新：playground-v25, 43.6 , 67.5 , 83.3 # sd30_medium, 42.3 , 71.0 # sd35_medium, 42.8 , 66.4 # sd35_large, 44.6 , 72.3 # emu3, 33.8 , 54.7 # janus_pro_7B, 37.1 , 63.3 # show-o-512, 32.9 , 62.0 # GoT, 30.8 , 50.9 # bagel, 52.1 , 70.9 # 从25开始错误: Gemini, 13.4 , 22.9 更新后： # 从104开始错误: GPT, 42.2 , 57.5 更新后： #整体 # hidream, 45.0 , 72.5 , 84.5 # flux1-dev, 38.8 , 65.1 , 80.9 # flux1-schnell, 41.2 , 73.0 , 83.0 # playground-v25, 43.6 , 67.5 , 83.3 # sd30_medium, 42.3 , 71.0 , 81.7 # sd35_medium, 42.8 , 66.4 , 83.0 # sd35_large, 44.6 , 72.3 , 84.5 # emu3, 33.8 , 54.7 , 77.0 # janus_pro_7B, 37.1 , 63.3 , 77.8 # show-o-512, 32.9 , 62.0 , 76.6 # GoT, 30.8 , 50.9 , 76.3 # bagel, 52.1 , 70.9 , 88.3 # Gemini, 60.7 , 80.7 , 89.3 # GPT, 68.7 , 88.5 , 94.3 # ！！！整体 0.7 0.3 # hidream, 53.2 , 84.5 # flux1-dev, 46.7 , 80.9 # flux1-schnell, 50.7 , 83.0 # playground-v25, 50.8 , 83.3 # sd30_medium, 50.9 , 81.7 # sd35_medium, 49.9 , 83.0 # sd35_large, 52.9 , 84.5 # emu3, 40.1 , 77.0 # janus_pro_7B, 44.9 , 77.8 # show-o-512, 41.6 , 76.6 # GoT, 36.8 , 76.3 # bagel, 57.7 , 88.3 # Gemini, 66.7 , 89.3 # GPT, 74.7 , 94.3 # qwen_image, 61.0 , 87.5 # physics pipeline # hidream, 63.3 , 76.6 # 有错误：flux1-dev, 64.4 , 79.1 更新后，有一个测不出来【149】：64.8 , 79.2 , 92.3 # 有错误,40测不出来：flux1-schnell, 62.5 , 75.5, 更新：flux1-schnell, 62.2 , 75.4 # playground-v25, 52.5 , 64.8 # sd30_medium, 60.6 , 77.1 # sd35_medium, 63.2 , 74.4 # sd35_large, 65.2 , 76.4 # janus_pro_7B, 56.7 , 71.4 # show-o-512, 55.9 , 69.2 # GoT, 38.7 , 54.9 # bagel, 63.6 , 76.7 # GPT, 78.8 , 85.4 # 整体 # hidream, 63.3 , 76.6 , 89.9 # flux1-dev, 64.8 , 79.2 , 92.3 # flux1-schnell, 62.2 , 75.4 , 90.1 # playground-v25, 52.5 , 64.8 , 87.0 # sd30_medium, 60.6 , 77.1 , 91.7 # sd35_medium, 63.2 , 74.4 , 89.9 # sd35_large, 65.2 , 76.4 , 92.3 # emu3, 44.7 , 57.4 , 84.1 # janus_pro_7B, 56.7 , 71.4 , 87.5 # show-o-512, 55.9 , 69.2 , 90.3 # GoT, 38.7 , 54.9 , 81.8 # bagel, 63.6 , 76.7 , 90.3 # Gemini, 69.2 , 78.9 , 90.6 # GPT, 78.8 , 85.4 , 95.4 # !!! 整体 0.7, 0.3 # hidream, 67.3 , 89.9 # flux1-dev, 69.1 , 92.3 # flux1-schnell, 66.1 , 90.1 # playground-v25, 56.1 , 87.0 # sd30_medium, 65.5 , 91.7 # sd35_medium, 66.6 , 89.9 # sd35_large, 68.6 , 92.3 # emu3, 48.5 , 84.1 # janus_pro_7B, 61.1 , 87.5 # show-o-512, 59.9 , 90.3 # GoT, 43.6 , 81.8 # bagel, 67.5 , 90.3 # Gemini, 72.1 , 90.6 # GPT, 80.8 , 95.4