Update app.py

app.py

@@ -1,7 +1,58 @@
-import gradio as gr
+from fastapi import FastAPI, File, UploadFile
+import numpy as np
+from PIL import Image
+from paddleocr import PaddleOCR
+from doctr.io import DocumentFile
+from doctr.models import ocr_predictor
+import io
 
-def greet(name):
-    return "Hello " + name + "!!"
+app = FastAPI()
 
-demo = gr.Interface(fn=greet, inputs="text", outputs="text")
-demo.launch()
+# Load the doctr OCR model
+ocr_model = ocr_predictor(pretrained=True)
+
+def ocr_with_doctr(file):
+    text_output = ''
+    
+    # Load the document
+    doc = DocumentFile.from_pdf(file)
+    
+    # Perform OCR
+    result = ocr_model(doc)
+    
+    # Extract text from OCR result
+    for page in result.pages:
+        for block in page.blocks:
+            for line in block.lines:
+                text_output += " ".join([word.value for word in line.words]) + "\n"
+    
+    return text_output
+
+def ocr_with_paddle(img):
+    finaltext = ''
+    ocr = PaddleOCR(lang='en', use_angle_cls=True)
+    result = ocr.ocr(img)
+    
+    for i in range(len(result[0])):
+        text = result[0][i][1][0]
+        finaltext += ' ' + text
+    return finaltext
+
+
+def generate_text_from_image(img):
+    text_output = ''
+    text_output = ocr_with_paddle(img)
+    return text_output
+
+@app.post("/ocr/")
+async def perform_ocr(file: UploadFile = File(...)):
+   
+    file_bytes = await file.read()
+    
+    if file.filename.endswith('.pdf'):
+        text_output = ocr_with_doctr(io.BytesIO(file_bytes))
+    else:
+        img = np.array(Image.open(io.BytesIO(file_bytes)))
+        text_output = generate_text_from_image(img)
+
+    return {"ocr_text": text_output}