Update my_model/tabs/run_inference.py

my_model/tabs/run_inference.py

@@ -29,16 +29,6 @@ sample_images = ["Files/sample1.jpg", "Files/sample2.jpg", "Files/sample3.jpg",
 
 
 
-def analyze_image(image, model):
-    
-    img = copy.deepcopy(image)  # we dont wanna apply changes to the original image
-    caption = model.get_caption(img)
-    image_with_boxes, detected_objects_str = model.detect_objects(img)
-    st.text("I am ready, let's talk!")
-    free_gpu_resources()
-    
-    return caption, detected_objects_str, image_with_boxes
-    
 
 def image_qa_app(kbvqa):
     # Display sample images as clickable thumbnails
@@ -82,16 +72,6 @@ def image_qa_app(kbvqa):
 
 
 
-def process_new_image(image_key, image, kbvqa):
-    """Process a new image and update the session state."""
-    if image_key not in st.session_state['images_data']:
-        st.session_state['images_data'][image_key] = {
-            'image': image,
-            'caption': '',
-            'detected_objects_str': '',
-            'qa_history': [],
-            'analysis_done': False
-        }
 
 def run_inference():
     
@@ -116,8 +96,8 @@ def run_inference():
                 state_manager.reload_detection_model()
                 st.success("Model reloaded with updated settings and ready for inference.")
 
-            if state_manager.is_model_loaded() and st.session_state.kbvqa.all_models_loaded:
-                image_qa_app(state_manager.get_model())
+        if state_manager.is_model_loaded() and st.session_state.kbvqa.all_models_loaded:
+            image_qa_app(state_manager.get_model())
 
      
             st.write(st.session_state.kbvqa.all_models_loaded)
@@ -126,17 +106,4 @@ def run_inference():
         st.write('Model is not ready yet, will be updated later.')
 
 
-def display_model_settings():
-    st.write("### Current Model Settings:")
-    st.table(pd.DataFrame(st.session_state['model_settings'], index=[0]))
-
-def display_session_state():
-    st.write("### Current Session State:")
-    # Convert session state to a list of dictionaries, each representing a row
-    data = [{'Key': key, 'Value': str(value)} for key, value in st.session_state.items()]
-    # Create a DataFrame from the list
-    df = pd.DataFrame(data)
-    st.table(df)
-
-