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README.md

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+📦 CAPTCHA Datasets (style0–style59)
+====================================
+
+This repository contains CAPTCHA datasets for training CRNN+CTC models. Each archive `dataset_*.tar.gz` includes **60 styles** (from [BotDetect Captcha](https://captcha.com/)), structured as folders `style0` through `style59`. Each style contains _N_ images depending on the archive name.
+
+* * *
+
+🗂️ Available Archives
+----------------------
+
+*   `dataset_500.tar.gz` → 500 images per style (≈ 30,000 total)
+*   `dataset_1000.tar.gz` → 1,000 images per style (≈ 60,000 total)
+*   `dataset_5000.tar.gz` → 5,000 images per style (≈ 300,000 total)
+*   `dataset_10000.tar.gz` → 10,000 images per style (≈ 600,000 total)
+*   `dataset_20000.tar.gz` → 20,000 images per style (≈ 1,200,000 total)
+*   `dataset_1000_rand.tar.gz` → randomized variant with 1,000 images per style
+
+**Naming convention:** `dataset_{N}.tar.gz` means each `styleX` folder holds exactly `N` PNG images.
+
+* * *
+
+📁 Directory Layout
+-------------------
+
+    /path/to/dataset
+    ├── style0/
+    │   ├── A1B2C.png
+    │   ├── 9Z7QK.png
+    │   └── ...
+    ├── style1/
+    │   ├── K9NO2.png
+    │   └── ...
+    └── ...
+        └── style59/
+    
+
+*   **Filename** = ground-truth label (5 uppercase alphanumeric chars), e.g. `K9NO2.png`.
+*   **Image size** = `50×250` pixels (H=50, W=250), grayscale PNG.
+*   **Label rule** = regex `^[A-Z0-9]{5}$` (exactly 5 chars, uppercase & digits).
+
+* * *
+
+🧰 Extraction
+-------------
+
+    # example: extract into /workspace/dataset_1000
+    mkdir -p /workspace/dataset_1000
+    tar -xvzf dataset_1000.tar.gz -C /workspace/dataset_1000
+    
+
+* * *
+
+✅ Quick File Counts
+-------------------
+
+    # total PNG files (depth 2 to only count inside style folders)
+    find /workspace/dataset_1000 -maxdepth 2 -type f -name '*.png' | wc -l
+    
+    # per-style counts without a for-loop (prints "count styleX")
+    find /workspace/dataset_1000 -mindepth 2 -maxdepth 2 -type f -name '*.png' \
+    | awk -F/ '{print $(NF-2)}' | sort | uniq -c | sort -k2
+    
+
+Expected totals:
+
+*   `dataset_500` → 500 × 60 = 30,000 files
+*   `dataset_1000` → 60,000 files
+*   `dataset_5000` → 300,000 files
+*   `dataset_10000` → 600,000 files
+*   `dataset_20000` → 1,200,000 files
+
+* * *
+
+🧪 Label Validation
+-------------------
+
+    # list filenames that violate the strict 5-char uppercase/digit rule
+    find /workspace/dataset_1000 -type f -name '*.png' \
+    | awk -F/ '{print $NF}' | sed 's/\.png$//' \
+    | grep -vE '^[A-Z0-9]{5}$' | head
+    
+
+CSV report via Python (pandas):
+
+    import os, re
+    import pandas as pd
+    from glob import glob
+    
+    root = "/workspace/dataset_1000"
+    rows = []
+    for s in range(60):
+        for p in glob(os.path.join(root, f"style{s}", "*.png")):
+            rows.append({"style": f"style{s}", "filepath": p, "label": os.path.basename(p)[:-4]})
+    
+    df = pd.DataFrame(rows)
+    bad = df[~df["label"].str.match(r"^[A-Z0-9]{5}$", na=True)]
+    print("Invalid labels:", len(bad))
+    if len(bad):
+        bad.to_csv("invalid_labels.csv", index=False)
+    
+
+* * *
+
+🧩 Example: Load to DataFrame
+-----------------------------
+
+    import os
+    from glob import glob
+    import pandas as pd
+    
+    def load_dataset(root_dir):
+        data = []
+        for style_id in range(60):
+            folder = os.path.join(root_dir, f"style{style_id}")
+            for path in glob(os.path.join(folder, "*.png")):
+                label = os.path.splitext(os.path.basename(path))[0]
+                data.append((path, label, f"style{style_id}"))
+        df = pd.DataFrame(data, columns=["filepath", "label", "style"])
+        # enforce strict label rule
+        df = df[df["label"].str.match(r"^[A-Z0-9]{5}$")]
+        return df
+    
+    df = load_dataset("/workspace/dataset_1000")
+    print(df.head(), len(df))
+    
+
+* * *
+
+🔀 Merge Datasets (no loop)
+---------------------------
+
+**Add new files without overwriting existing ones**:
+
+    rsync -av \
+      --ignore-existing \
+      --include='style[0-5][0-9]/' \
+      --include='style[0-5][0-9]/*.png' \
+      --exclude='*' \
+      /workspace/dataset_10000/  /workspace/dataset_20000/
+    
+
+**Overwrite only if source is newer**:
+
+    rsync -av --update \
+      --include='style[0-5][0-9]/' \
+      --include='style[0-5][0-9]/*.png' \
+      --exclude='*' \
+      /workspace/dataset_10000/  /workspace/dataset_20000/
+    
+
+* * *
+
+🔒 Checksums
+------------
+
+Optional: keep SHA256 for integrity.
+
+    sha256sum dataset_1000.tar.gz > dataset_1000.tar.gz.sha256
+    sha256sum -c dataset_1000.tar.gz.sha256
+    
+
+* * *
+
+📝 Notes
+--------
+
+*   All images prepared for CRNN+CTC models with input `(H, W) = (50, 250)`, grayscale.
+*   Character distribution: digits 0–9 and letters A–Z (uppercase).
+*   Each style emulates a distinct visual variant (font/noise/warp) from BotDetect.
+
+* * *
+
+📞 Contact
+----------
+
+For questions, dataset issues, or custom subsets, please open an issue in this repository.

dataset_10000.tar.gz

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dataset_1000_rand.tar.gz

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dataset_20000.tar.gz

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+size 6094405204

dataset_500.tar.gz

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+size 138296823

dataset_5000.tar.gz

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