Update app.py

Modify predict_text() to Split the Image

app.py

@@ -19,14 +19,24 @@ def preprocess_image(image):
 
 # Function to predict text from handwritten prescription
 def predict_text(image):
-    processed_image = preprocess_image(image)
-    prediction = model.predict(processed_image)
-    
-    print("Model output shape:", prediction.shape)  # Should be (1, sequence_length, num_classes) ideally
-    print("Model output values:", prediction)  # Print raw output for analysis
-
-    predicted_text = decode_prediction(prediction)
-    return predicted_text
+    image = image.convert("RGB")
+    image = image.resize((128, 64))  # Resize for better character separation
+    image = np.array(image) / 255.0  # Normalize
+
+    num_chars = 5  # Estimate word length
+    segment_width = image.shape[1] // num_chars  # Split image into equal parts
+
+    predicted_text = []
+    for i in range(num_chars):
+        char_segment = image[:, i * segment_width:(i + 1) * segment_width, :]
+        char_segment = np.expand_dims(char_segment, axis=0)  # Add batch dimension
+
+        # Predict character for each segment
+        prediction = model.predict(char_segment)
+        char = decode_prediction(prediction)
+        predicted_text.append(char)
+
+    return "".join(predicted_text)
 
 
 import numpy as np