Implemented OCR decoding for prescription text

app.py

@@ -24,10 +24,16 @@ def predict_text(image):
     print(prediction)  # Check what the model is outputting
     predicted_text = decode_prediction(prediction)  # Implement your decoding logic
     return predicted_text
+import string
+
+# Define possible characters in prescriptions (letters, numbers, etc.)
+CHARACTER_SET = string.ascii_letters + string.digits + " .,-/()"
 
 # Placeholder function for decoding (depends on model architecture)
 def decode_prediction(prediction):
-    return "Decoded text (implement OCR logic)"
+    indices = np.argmax(prediction, axis=-1)  # Get index of highest probability for each character
+    text = "".join([CHARACTER_SET[i] for i in indices[0]])  # Convert indices to characters
+    return text
 
 # Gradio UI
 interface = gr.Interface(