chore: import upstream snapshot with attribution

2026-07-13 13:24:13 +08:00
commit 1037506f2e
6050 changed files with 1731598 additions and 0 deletions
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+# ------------------------------------------
+# TextDiffuser: Diffusion Models as Text Painters
+# Paper Link: https://arxiv.org/abs/2305.10855
+# Code Link: https://github.com/microsoft/unilm/tree/master/textdiffuser
+# Copyright (c) Microsoft Corporation.
+# This file provides the inference script.
+# ------------------------------------------
+
+import os
+import re
+import copy
+
+gts = {
+    'ChineseDrawText': [],
+    'DrawBenchText': [],
+    'DrawTextCreative': [],
+    'LAIONEval4000': [],
+    'OpenLibraryEval500': [],
+    'TMDBEval500': [],
+}
+
+results = {
+    'stablediffusion': {'cnt':0, 'p':0, 'r':0, 'f':0, 'acc':0},
+    'textdiffuser': {'cnt':0, 'p':0, 'r':0, 'f':0, 'acc':0},
+    'controlnet': {'cnt':0, 'p':0, 'r':0, 'f':0, 'acc':0},
+    'deepfloyd': {'cnt':0, 'p':0, 'r':0, 'f':0, 'acc':0},
+}
+
+def get_key_words(text: str):
+    words = []
+    text = text
+    matches = re.findall(r"'(.*?)'", text) # find the keywords enclosed by ''
+    if matches:
+        for match in matches:
+            words.extend(match.split())
+   
+    return words
+
+
+# load gt
+files = os.listdir('/path/to/MARIOEval')
+for file in files:
+    lines = open(os.path.join('/path/to/MARIOEval', file, f'{file}.txt')).readlines()
+    for line in lines:
+        line = line.strip().lower()
+        gts[file].append(get_key_words(line))
+print(gts['ChineseDrawText'][:10])
+
+
+def get_p_r_acc(method, pred, gt):
+
+    pred = [p.strip().lower() for p in pred] 
+    gt = [g.strip().lower() for g in gt]
+
+    pred_orig = copy.deepcopy(pred)
+    gt_orig = copy.deepcopy(gt)
+
+    pred_length = len(pred)
+    gt_length = len(gt)
+
+    for p in pred:
+        if p in gt_orig:
+            pred_orig.remove(p) 
+            gt_orig.remove(p)
+
+    p = (pred_length - len(pred_orig)) / (pred_length + 1e-8)
+    r = (gt_length - len(gt_orig)) / (gt_length + 1e-8)
+   
+    pred_sorted = sorted(pred)
+    gt_sorted = sorted(gt)
+    if ''.join(pred_sorted) == ''.join(gt_sorted):
+        acc = 1
+    else:
+        acc = 0
+
+    return p, r, acc
+
+
+files = os.listdir('/path/to/MaskTextSpotterV3/tools/ocr_result')
+print(len(files))
+
+for file in files:
+    method, dataset, prompt_index, image_index = file.strip().split('_')
+    ocrs = open(os.path.join('/path/to/MaskTextSpotterV3/tools/ocr_result', file)).readlines()
+    p, r, acc = get_p_r_acc(method, ocrs, gts[dataset][int(prompt_index)])
+    results[method]['cnt'] += 1
+    results[method]['p'] += p
+    results[method]['r'] += r
+    results[method]['acc'] += acc
+
+for method in results.keys():
+    results[method]['p'] /= results[method]['cnt']
+    results[method]['r'] /= results[method]['cnt']
+    results[method]['f'] = 2 * results[method]['p'] * results[method]['r'] / (results[method]['p'] + results[method]['r'] + 1e-8)
+    results[method]['acc'] /= results[method]['cnt']
+    
+print(results)
+