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README.md

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+# OCR (CPU/GPU)
+
+- **Model:** `easyocr` (Apache-2.0)
+- **Task:** Extract text from images. Default language: English.
+- **Note:** Here we just provide the resources for to run this models in the laptops we didn't develop this entire models we just use the open source models for the experiment this model is developed by Jaided AI
+
+## Quick start (any project)
+
+```bash
+# 1) Create env
+python -m venv venv && source .venv/bin/activate  # Windows: ./venv/Scripts/activate
+
+# 2) Install deps
+pip install -r requirements.txt
+
+# 3) Run
+python main.py --help
+```
+
+> Tip: If you have a GPU + CUDA, PyTorch will auto-use it. If not, everything runs on CPU (slower but works).
+
+---
+
+here if you face conflicts when downloading the model using main.py then reinstall the library 
+**pip install numpy==1.26.4**
+
+and while running the main.py code using command then only you the output 
+**Use:** python main.py --image remiai.png or python main.py --image sample.jpg 
+
+other wise you get the output like this 
+usage: main.py [-h] --image IMAGE
+error: the following arguments are required: --image

main.py

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+import argparse 
+import easyocr
+from PIL import Image
+
+def main():
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--image", type=str, required=True)
+    args = parser.parse_args()
+
+    reader = easyocr.Reader(['en'], gpu=False)  # force CPU for universality
+    result = reader.readtext(args.image, detail=1)
+    for bbox, text, conf in result:
+        print(f"{text}\t{conf:.3f}")
+
+if __name__ == "__main__":
+    main()

requirements.txt

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+torch==2.1.0
+torchvision==0.16.0
+torchaudio==2.1.0
+transformers==4.38.2
+datasets==2.18.0
+Pillow==10.2.0
+numpy==1.26.4
+tqdm==4.66.2
+sentencepiece==0.1.99
+sentence-transformers==2.6.1
+easyocr==1.7.1