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Vanbitcase/
text-capcha-solver

Name: text-capcha-solver
Rating: 2.5 (12 reviews)

safetensors

vision-encoder-decoder

custom-captcha-dataset

microsoft/trocr-base-printed

finetune

apache-2.0

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anuashok/ocr-captcha-v3

This model is a fine-tuned version of microsoft/trocr-base-printed on Captchas of the type shown below

Training Summary

CER (Character Error Rate): 0.01394585726004922
Hyperparameters:
- Learning Rate: 1.5078922700531405e-05
- Batch Size: 16
- Num Epochs: 7
- Warmup Ratio: 0.14813004670666596
- Weight Decay: 0.017176551931326833
- Num Beams: 2
- Length Penalty: 1.3612823161368288

Usage

python

from transformers import VisionEncoderDecoderModel, TrOCRProcessor
import torch
from PIL import Image

# Load model and processor
processor = TrOCRProcessor.from_pretrained("anuashok/ocr-captcha-v3")
model = VisionEncoderDecoderModel.from_pretrained("anuashok/ocr-captcha-v3")

# Load image
image = Image.open('path_to_your_image.jpg').convert("RGB")
# Load and preprocess image for display
image = Image.open(image_path).convert("RGBA")
# Create white background
background = Image.new("RGBA", image.size, (255, 255, 255))
combined = Image.alpha_composite(background, image).convert("RGB")

# Prepare image
pixel_values = processor(combined, return_tensors="pt").pixel_values

# Generate text
generated_ids = model.generate(pixel_values)
generated_text = processor.batch_decode(generated_ids, skip_special_tokens=True)[0]
print(generated_text)

Vanbitcase/text-capcha-solver

anuashok/ocr-captcha-v3

Training Summary

Usage

Vanbitcase/
text-capcha-solver