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Update my_model/state_manager.py
Browse files- my_model/state_manager.py +15 -1
my_model/state_manager.py
CHANGED
@@ -24,7 +24,7 @@ class StateManager:
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def set_up_widgets(self):
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# Create two columns with different widths
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-
col1, col2 = st.columns([0.
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with col1:
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st.selectbox("Choose a method:", ["Fine-Tuned Model", "In-Context Learning (n-shots)"], index=0, key='method')
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detection_model = st.selectbox("Choose a model for objects detection:", ["yolov5", "detic"], index=1, key='detection_model')
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@@ -37,15 +37,19 @@ class StateManager:
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if show_model_settings:
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self.display_model_settings()
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def set_slider_value(self, text, min_value, max_value, value, step, slider_key_name):
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return st.slider(text, min_value, max_value, value, step, key=slider_key_name)
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@property
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def settings_changed(self):
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return self.has_state_changed()
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def display_model_settings(self):
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st.write("#### Current Model Settings:")
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data = [{'Key': key, 'Value': str(value)} for key, value in st.session_state.items() if key in ["confidence_level", 'detection_model', 'method', 'kbvqa', 'previous_state', 'settings_changed', ]]
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@@ -53,11 +57,13 @@ class StateManager:
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styled_df = df.style.set_properties(**{'background-color': 'black', 'color': 'white', 'border-color': 'white'}).set_table_styles([{'selector': 'th','props': [('background-color', 'black'), ('font-weight', 'bold')]}])
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st.table(styled_df)
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def display_session_state(self):
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st.write("Current Model:")
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data = [{'Key': key, 'Value': str(value)} for key, value in st.session_state.items()]
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df = pd.DataFrame(data)
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st.table(df)
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def load_model(self):
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"""Load the KBVQA model with specified settings."""
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@@ -76,6 +82,7 @@ class StateManager:
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except Exception as e:
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st.error(f"Error loading model: {e}")
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# Function to check if any session state values have changed
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def has_state_changed(self):
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for key in st.session_state['previous_state']:
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@@ -83,13 +90,16 @@ class StateManager:
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return True # Found a change
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else: return False # No changes found
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def get_model(self):
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"""Retrieve the KBVQA model from the session state."""
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return st.session_state.get('kbvqa', None)
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def is_model_loaded(self):
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return 'kbvqa' in st.session_state and st.session_state['kbvqa'] is not None
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def reload_detection_model(self):
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try:
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free_gpu_resources()
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@@ -112,6 +122,7 @@ class StateManager:
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'analysis_done': False
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}
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def analyze_image(self, image, kbvqa):
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img = copy.deepcopy(image)
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st.text("Analyzing the image .. ")
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@@ -119,13 +130,16 @@ class StateManager:
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image_with_boxes, detected_objects_str = kbvqa.detect_objects(img)
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return caption, detected_objects_str, image_with_boxes
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def add_to_qa_history(self, image_key, question, answer):
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if image_key in st.session_state['images_data']:
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st.session_state['images_data'][image_key]['qa_history'].append((question, answer))
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def get_images_data(self):
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return st.session_state['images_data']
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def update_image_data(self, image_key, caption, detected_objects_str, analysis_done):
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if image_key in st.session_state['images_data']:
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st.session_state['images_data'][image_key].update({
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def set_up_widgets(self):
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# Create two columns with different widths
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col1, col2, col3 = st.columns([0.2, 0.6, 0.2]) # Adjust the ratio as needed
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with col1:
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st.selectbox("Choose a method:", ["Fine-Tuned Model", "In-Context Learning (n-shots)"], index=0, key='method')
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detection_model = st.selectbox("Choose a model for objects detection:", ["yolov5", "detic"], index=1, key='detection_model')
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if show_model_settings:
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self.display_model_settings()
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col3.header("COL3")
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def set_slider_value(self, text, min_value, max_value, value, step, slider_key_name):
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return st.slider(text, min_value, max_value, value, step, key=slider_key_name)
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+
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@property
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def settings_changed(self):
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return self.has_state_changed()
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def display_model_settings(self):
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st.write("#### Current Model Settings:")
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data = [{'Key': key, 'Value': str(value)} for key, value in st.session_state.items() if key in ["confidence_level", 'detection_model', 'method', 'kbvqa', 'previous_state', 'settings_changed', ]]
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styled_df = df.style.set_properties(**{'background-color': 'black', 'color': 'white', 'border-color': 'white'}).set_table_styles([{'selector': 'th','props': [('background-color', 'black'), ('font-weight', 'bold')]}])
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st.table(styled_df)
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def display_session_state(self):
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st.write("Current Model:")
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data = [{'Key': key, 'Value': str(value)} for key, value in st.session_state.items()]
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df = pd.DataFrame(data)
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st.table(df)
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def load_model(self):
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"""Load the KBVQA model with specified settings."""
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except Exception as e:
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st.error(f"Error loading model: {e}")
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# Function to check if any session state values have changed
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def has_state_changed(self):
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for key in st.session_state['previous_state']:
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return True # Found a change
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else: return False # No changes found
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def get_model(self):
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"""Retrieve the KBVQA model from the session state."""
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return st.session_state.get('kbvqa', None)
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def is_model_loaded(self):
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return 'kbvqa' in st.session_state and st.session_state['kbvqa'] is not None
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def reload_detection_model(self):
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try:
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free_gpu_resources()
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'analysis_done': False
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}
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def analyze_image(self, image, kbvqa):
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img = copy.deepcopy(image)
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st.text("Analyzing the image .. ")
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image_with_boxes, detected_objects_str = kbvqa.detect_objects(img)
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return caption, detected_objects_str, image_with_boxes
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def add_to_qa_history(self, image_key, question, answer):
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if image_key in st.session_state['images_data']:
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st.session_state['images_data'][image_key]['qa_history'].append((question, answer))
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def get_images_data(self):
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return st.session_state['images_data']
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def update_image_data(self, image_key, caption, detected_objects_str, analysis_done):
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if image_key in st.session_state['images_data']:
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st.session_state['images_data'][image_key].update({
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