Update app.py

app.py

@@ -1,6 +1,7 @@
 import gradio as gr
 import json
 from PIL import Image
+# Assuming these imports work as expected, but you might need to adjust based on your actual package structure
 from surya.ocr import run_ocr
 from surya.detection import batch_detection
 from surya.model.detection.segformer import load_model as load_det_model, load_processor as load_det_processor
@@ -8,34 +9,35 @@ from surya.model.recognition.model import load_model as load_rec_model
 from surya.model.recognition.processor import load_processor as load_rec_processor
 from surya.postprocessing.heatmap import draw_polys_on_image
 
-# Load models and processors
+# Load models and processors with print statements to confirm loading
+print("Loading models and processors...")
 det_model, det_processor = load_det_model(), load_det_processor()
 rec_model, rec_processor = load_rec_model(), load_rec_processor()
+print("Models and processors loaded successfully.")
 
-# Create a dictionary to map language names to codes
+# Load language codes
+print("Loading language codes...")
 with open("languages.json", "r") as file:
     languages = json.load(file)
 language_dict = {name: code for name, code in languages.items()}
-
-# Use the language names for the dropdown choices
-language_options = list(language_dict.keys())
+print(f"Loaded languages: {list(language_dict.keys())}")
 
 def ocr_function(img, lang_name):
-    print(f"OCR Function Called with lang_name: {lang_name}")  # Debug print
-    # Get the language code from the dictionary
+    print(f"OCR Function Called with lang_name: {lang_name}")
     lang_code = language_dict[lang_name]
-    print(f"Language Code: {lang_code}")  # Debug print
+    print(f"Language Code: {lang_code}")
     predictions = run_ocr([img], [lang_code], det_model, det_processor, rec_model, rec_processor)
-    print(f"Predictions: {predictions}")  # Debug print
+    print(f"Predictions: {predictions}")
     if predictions:
         img_with_text = draw_polys_on_image(predictions[0]["polys"], img)
         return img_with_text, predictions[0]["text"]
     else:
         return img, "No text detected"
 
-
 def text_line_detection_function(img):
+    print("Text Line Detection Function Called")
     preds = batch_detection([img], det_model, det_processor)[0]
+    print(f"Detection Predictions: {preds}")
     img_with_lines = draw_polys_on_image(preds["polygons"], img)
     return img_with_lines, preds
 
@@ -44,13 +46,12 @@ with gr.Blocks() as app:
     with gr.Tab("OCR"):
         with gr.Column():
             ocr_input_image = gr.Image(label="Input Image for OCR", type="pil")
-            ocr_language_selector = gr.Dropdown(label="Select Language for OCR", choices=language_options, value="English")
+            ocr_language_selector = gr.Dropdown(label="Select Language for OCR", choices=list(language_dict.keys()), value="English")
             ocr_run_button = gr.Button("Run OCR")
         with gr.Column():
             ocr_output_image = gr.Image(label="OCR Output Image", type="pil", interactive=False)
             ocr_text_output = gr.TextArea(label="Recognized Text")
 
-        # Pass the input image and the language name to the ocr_function
         ocr_run_button.click(fn=ocr_function, inputs=[ocr_input_image, ocr_language_selector], outputs=[ocr_output_image, ocr_text_output])
 
     with gr.Tab("Text Line Detection"):
@@ -61,7 +62,6 @@ with gr.Blocks() as app:
             detection_output_image = gr.Image(label="Detection Output Image", type="pil", interactive=False)
             detection_json_output = gr.JSON(label="Detection JSON Output")
 
-        # Pass the input image to the text_line_detection_function
         detection_run_button.click(fn=text_line_detection_function, inputs=detection_input_image, outputs=[detection_output_image, detection_json_output])
 
 if __name__ == "__main__":