Implement OCR functionality with Gradio interface and model downloads

app.py

@@ -1,7 +1,54 @@
 import gradio as gr
+import numpy as np
+import cv2
+import onnxruntime as ort
+import os
+from huggingface_hub import hf_hub_download
 
-def greet(name):
-    return "Hello " + name + "!!"
+# Function to download model files from Hugging Face
+def download_model_files():
+    model_repo = "SWHL/RapidOCR"
+    det_model_filename = "PP-OCRv4/en_PP-OCRv3_det_infer.onnx"
+    rec_model_filename = "PP-OCRv4/ch_PP-OCRv4_rec_server_infer.onnx"
+    cls_model_filename = "PP-OCRv3/ch_ppocr_mobile_v2.0_cls_train.onnx"
 
-demo = gr.Interface(fn=greet, inputs="text", outputs="text")
-demo.launch()
+    det_model_path = hf_hub_download(repo_id=model_repo, filename=det_model_filename)
+    rec_model_path = hf_hub_download(repo_id=model_repo, filename=rec_model_filename)
+    cls_model_path = hf_hub_download(repo_id=model_repo, filename=cls_model_filename)
+
+    return det_model_path, rec_model_path, cls_model_path
+
+# Download model files
+det_model_path, rec_model_path, cls_model_path = download_model_files()
+
+# Load models
+det_session = ort.InferenceSession(det_model_path)
+rec_session = ort.InferenceSession(rec_model_path)
+cls_session = ort.InferenceSession(cls_model_path)
+
+def preprocess_image(image):
+    # Convert to grayscale
+    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+    # Resize or pad image to desired size if necessary
+    return gray
+
+def ocr_predict(image):
+    # Preprocess the image
+    preprocessed_image = preprocess_image(image)
+    # Perform detection, classification, and recognition using the ONNX models
+    # This is a placeholder for the actual OCR pipeline
+    # Replace with your model's inference code
+    text = "Detected text goes here"
+    return text
+
+# Define Gradio interface
+iface = gr.Interface(
+    fn=ocr_predict,
+    inputs=gr.Image(type="numpy", label="Upload Image"),
+    outputs=gr.Textbox(label="Detected Text"),
+    title="RapidOCR Gradio Demo",
+    description="Upload an image to extract text using RapidOCR."
+)
+
+if __name__ == "__main__":
+    iface.launch()

requirements.txt

@@ -0,0 +1,7 @@
+gradio
+transformers
+onnxruntime
+numpy
+opencv-python
+torch
+huggingface-hub