Show only columns

app.py

@@ -1,10 +1,7 @@
 import gradio as gr
-from huggingface_hub import hf_hub_download
-from PIL import Image
-import torch
 from transformers import AutoImageProcessor, AutoModelForObjectDetection
+import torch
 
-gr.load("models/microsoft/table-transformer-structure-recognition").launch()
 # Load the processor and model for table structure recognition
 processor = AutoImageProcessor.from_pretrained("microsoft/table-transformer-structure-recognition")
 model = AutoModelForObjectDetection.from_pretrained("microsoft/table-transformer-structure-recognition")
@@ -22,8 +19,12 @@ def predict(image):
     predicted_boxes = outputs.pred_boxes[0].cpu().numpy()  # First image
     predicted_classes = outputs.logits.argmax(-1).cpu().numpy()  # Class predictions
 
-    # Return the bounding boxes for display
-    return {"boxes": predicted_boxes.tolist(), "classes": predicted_classes.tolist()}
+    # Filter predictions to only include columns
+    column_class_id = 1  # Assuming class ID 1 corresponds to columns, adjust if needed
+    column_boxes = predicted_boxes[predicted_classes == column_class_id]
+    
+    # Return the bounding boxes for columns
+    return {"boxes": column_boxes.tolist(), "classes": ["column"] * len(column_boxes)}
 
 # Set up the Gradio interface
 interface = gr.Interface(
@@ -33,4 +34,4 @@ interface = gr.Interface(
 )
 
 # Launch the Gradio app
-interface.launch()
+interface.launch()