Create app.py

app.py

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+from fastapi import FastAPI, UploadFile, File, Query
+from fastapi.responses import JSONResponse
+import easyocr
+import numpy as np
+import cv2
+import time
+import requests
+from io import BytesIO
+from PIL import Image
+import os
+
+app = FastAPI(title="EasyOCR API")
+
+# Use /tmp for writable storage
+tmp_dir = "/tmp/EasyOCR"
+model_dir = os.path.join(tmp_dir, "models")
+user_net_dir = os.path.join(tmp_dir, "user_network")
+os.makedirs(model_dir, exist_ok=True)
+os.makedirs(user_net_dir, exist_ok=True)
+
+# Initialize reader with custom directories
+reader = easyocr.Reader(
+    ['en'],
+    gpu=False,
+    model_storage_directory=model_dir,
+    user_network_directory=user_net_dir
+)
+
+def read_image_from_url(url: str):
+    response = requests.get(url)
+    response.raise_for_status()
+    img = np.array(Image.open(BytesIO(response.content)).convert("RGB"))
+    return img
+
+def preprocess_image(image: np.ndarray) -> np.ndarray:
+    # Convert to grayscale
+    gray = cv2.cvtColor(image, cv2.COLOR_RGB2GRAY)
+
+    # Denoise slightly
+    gray = cv2.GaussianBlur(gray, (3, 3), 0)
+
+    # Adaptive threshold (makes text sharper)
+    thresh = cv2.adaptiveThreshold(
+        gray, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C,
+        cv2.THRESH_BINARY, 31, 2
+    )
+
+    return thresh
+
+@app.get("/")
+async def ocr_url(url: str = Query(None)):
+    start_time = time.time()
+
+    if not url:
+        return JSONResponse(
+            status_code=400,
+            content={"status": False, "error": "Provide ?url= for OCR."}
+        )
+
+    try:
+        image = read_image_from_url(url)
+
+        # Preprocess for better OCR
+        processed = preprocess_image(image)
+
+        # OCR
+        result = reader.readtext(processed)
+
+        # Format result (only text)
+        output = [r[1] for r in result]
+
+        end_time = time.time()
+        time_taken = round(end_time - start_time, 3)
+
+        return {
+            "status": True,
+            "time_taken": time_taken,
+            "results": output
+        }
+
+    except Exception as e:
+        return JSONResponse(
+            status_code=500,
+            content={"status": False, "error": str(e)}
+        )
+
+@app.post("/")
+async def ocr_file(file: UploadFile = File(...)):
+    start_time = time.time()
+
+    try:
+        image = np.array(Image.open(file.file).convert("RGB"))
+
+        # Preprocess for better OCR
+        processed = preprocess_image(image)
+
+        # OCR
+        result = reader.readtext(processed)
+
+        # Format result (only text)
+        output = [r[1] for r in result]
+
+        end_time = time.time()
+        time_taken = round(end_time - start_time, 3)
+
+        return {
+            "status": True,
+            "time_taken": time_taken,
+            "results": output
+        }
+
+    except Exception as e:
+        return JSONResponse(
+            status_code=500,
+            content={"status": False, "error": str(e)}
+        )