Update app.py

app.py

@@ -1,36 +1,59 @@
 import gradio as gr
-import pandas as pd
+import easyocr
+from deep_translator import GoogleTranslator
+from PIL import Image, ImageDraw, ImageFont
 import numpy as np
-import pickle
 
-def predict_diabetes(pregnancies, glucose, blood_pressure, skin_thickness, insulin, bmi, diabetes_pedigree_function, age):
-    # Load the model
-    with open("model.pkl", "rb") as f:
-        model = pickle.load(f)
+# Initialize reader with allowed lang_list only
+reader = easyocr.Reader(['en', 'hi', 'mr', 'ne'])
 
-    input_data = np.array([[pregnancies, glucose, blood_pressure, skin_thickness, insulin, bmi, diabetes_pedigree_function, age]])
-    prediction = model.predict(input_data)
-    result = "Diabetic" if prediction[0] == 1 else "Not Diabetic"
-    return result
+# Font path — works on HuggingFace
+FONT_PATH = "/usr/share/fonts/truetype/dejavu/DejaVuSans-Bold.ttf"
 
-# Gradio Interface
-description = "Diabetes Prediction Model - Enter your values below"
+def process_image(image, target_lang):
+    img_array = np.array(image)
 
-demo = gr.Interface(
-    fn=predict_diabetes,
+    # Run OCR safely
+    results = reader.readtext(img_array)
+
+    if not results:
+        return image, "No text detected"
+
+    final_translations = []
+    img_pil = image.convert("RGB")
+    draw = ImageDraw.Draw(img_pil)
+    font = ImageFont.truetype(FONT_PATH, size=20)
+
+    for (bbox, text, prob) in results:
+        if text.strip():
+            try:
+                translated = GoogleTranslator(source='auto', target=target_lang).translate(text)
+            except:
+                translated = "[Translation Error]"
+
+            final_translations.append(translated)
+
+            # Draw translation at top-left of bounding box
+            top_left = bbox[0]
+            draw.text((top_left[0], top_left[1] - 20), translated, fill=(255, 0, 0), font=font)
+
+    full_text = "\n".join(final_translations)
+    return img_pil, full_text
+
+# Gradio UI
+iface = gr.Interface(
+    fn=process_image,
     inputs=[
-        gr.Number(label="Pregnancies"),
-        gr.Number(label="Glucose"),
-        gr.Number(label="Blood Pressure"),
-        gr.Number(label="Skin Thickness"),
-        gr.Number(label="Insulin"),
-        gr.Number(label="BMI"),
-        gr.Number(label="Diabetes Pedigree Function"),
-        gr.Number(label="Age")
+        gr.Image(type="pil", label="Upload Image"),
+        gr.Textbox(label="Translate To (hi / en / mr / ne)")
+    ],
+    outputs=[
+        gr.Image(type="pil", label="Image with Translated Overlay"),
+        gr.Textbox(label="Translated Text Output")
     ],
-    outputs=gr.Text(label="Prediction"),
-    title="Diabetes Prediction",
-    description=description
+    title="Image Translator with Overlay",
+    description="Extract & translate text from an image (OCR + translation overlay)"
 )
 
-demo.launch()
+if __name__ == "__main__":
+    iface.launch()