Update main.py

main.py

@@ -1,52 +1,51 @@
+from fastapi import FastAPI
+from pydantic import BaseModel
 import easyocr
 import numpy as np
 from PIL import Image
 import cv2
-from fastapi import FastAPI
-
-app = FastAPI()
-
-@app.get("/")
-def read_root():
-    return {"Hello": "World!"}
-    
-# st.set_page_config(page_title="OCR Text Extractor", layout="centered")
-# st.title("🧠 Image to Text Detection (OCR)")
-# st.write("Upload an image to extract text more accurately!")
-
-# uploaded_file = st.file_uploader("Upload an image", type=["jpg", "jpeg", "png"])
-
-# def preprocess_image(image):
-#     # Convert to grayscale
-#     gray = cv2.cvtColor(image, cv2.COLOR_RGB2GRAY)
-    
-#     # Resize image to double the size (helps OCR sometimes)
-#     scale_percent = 200
-#     width = int(gray.shape[1] * scale_percent / 100)
-#     height = int(gray.shape[0] * scale_percent / 100)
-#     resized = cv2.resize(gray, (width, height), interpolation=cv2.INTER_LINEAR)
-    
-#     # Apply thresholding (binary black & white)
-#     _, thresh = cv2.threshold(resized, 150, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)
-    
-#     return thresh
-
-# if uploaded_file:
-#     image = Image.open(uploaded_file).convert("RGB")
-#     st.image(image, caption="Original Image", use_container_width=True)
-
-#     img_np = np.array(image)
-#     processed_img = preprocess_image(img_np)
-
-#     st.image(processed_img, caption="Preprocessed Image", use_container_width=True, channels="GRAY")
-
-#     # OCR
-#     reader = easyocr.Reader(['en'], gpu=False)
-#     results = reader.readtext(processed_img)
-
-#     st.subheader("📃 Extracted Text:")
-#     if results:
-#         for bbox, text, prob in results:
-#             st.write(f"- {text}")
-#     else:
-#         st.warning("❌ No text found.")
+import base64
+import io
+
+app = FastAPI(title="OCR Base64 API")
+
+# Initialisation du lecteur EasyOCR (comme ton code)
+reader = easyocr.Reader(['en'], gpu=False)
+
+# Modèle de requête
+class ImageRequest(BaseModel):
+    image_base64: str  # Image encodée en Base64
+
+def preprocess_image(image):
+    gray = cv2.cvtColor(image, cv2.COLOR_RGB2GRAY)
+    scale_percent = 200
+    width = int(gray.shape[1] * scale_percent / 100)
+    height = int(gray.shape[0] * scale_percent / 100)
+    resized = cv2.resize(gray, (width, height), interpolation=cv2.INTER_LINEAR)
+    _, thresh = cv2.threshold(resized, 150, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)
+    return thresh
+
+@app.post("/extract-text/")
+def extract_text(request: ImageRequest):
+    try:
+        # Supprimer le préfixe si présent
+        b64_data = request.image_base64
+        if "base64," in b64_data:
+            b64_data = b64_data.split("base64,")[1]
+
+        # Décoder le Base64
+        image_bytes = base64.b64decode(b64_data)
+        image = Image.open(io.BytesIO(image_bytes)).convert("RGB")
+        img_np = np.array(image)
+
+        # Prétraitement
+        processed_img = preprocess_image(img_np)
+
+        # OCR
+        results = reader.readtext(processed_img)
+        extracted_text = [text.replace(" ", "") for _, text, _ in results]
+
+        return {"text": extracted_text}
+
+    except Exception as e:
+        return {"error": str(e)}