Update my_model/state_manager.py
Browse files- my_model/state_manager.py +119 -49
my_model/state_manager.py
CHANGED
@@ -1,3 +1,7 @@
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import pandas as pd
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import copy
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import time
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@@ -8,25 +12,25 @@ from my_model.utilities.gen_utilities import free_gpu_resources
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from my_model.KBVQA import KBVQA, prepare_kbvqa_model
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class StateManager:
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-
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# initialize_state: Initializes default values for session state.
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# set_up_widgets: Creates UI elements for model selection and settings.
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# set_slider_value: Generates a slider widget for numerical input.
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# is_widget_disabled: Returns True if UI elements should be disabled.
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# disable_widgets: Disables interactive UI elements during processing.
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# settings_changed: Checks if any model settings have changed.
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# confidance_change: Determines if the confidence level setting has changed.
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# display_model_settings: Shows current model settings in the UI.
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# display_session_state: Displays the current state of the application.
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# update_prev_state: Updates the record of the previous application state.
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# force_reload_model: Reloads the model, clearing and resetting necessary states.
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def __init__(self):
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"""
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Initializes the StateManager instance, setting up the Streamlit columns for the user interface.
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"""
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@@ -34,10 +38,12 @@ class StateManager:
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# Create three columns with different widths
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self.col1, self.col2, self.col3 = st.columns([0.2, 0.6, 0.2])
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-
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"""
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Initializes the Streamlit session state with default values for various keys.
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"""
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if "previous_state" not in st.session_state:
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st.session_state['previous_state'] = {'method': None, 'detection_model': None, 'confidence_level': None}
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if 'images_data' not in st.session_state:
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@@ -59,9 +65,13 @@ class StateManager:
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if 'model_loaded' not in st.session_state:
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st.session_state['model_loaded'] = self.is_model_loaded
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def set_up_widgets(self) -> None:
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"""
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Sets up user interface widgets for selecting models, settings, and displaying model settings conditionally.
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"""
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self.col1.selectbox("Choose a model:", ["13b-Fine-Tuned Model", "7b-Fine-Tuned Model", "Vision-Language Embeddings Alignment"], index=1, key='method', disabled=self.is_widget_disabled)
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@@ -70,14 +80,11 @@ class StateManager:
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self.set_slider_value(text="Select minimum detection confidence level", min_value=0.1, max_value=0.9, value=default_confidence, step=0.05, slider_key_name='confidence_level', col=self.col1)
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# Conditional display of model settings
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show_model_settings = self.col3.checkbox("Show Model Settings", True, disabled=self.is_widget_disabled)
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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: str, min_value: float, max_value: float, value: float, step: float, slider_key_name: str, col=None) -> None:
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"""
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Creates a slider widget with the specified parameters, optionally placing it in a specific column.
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@@ -90,6 +97,9 @@ class StateManager:
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step (float): Step size for the slider.
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slider_key_name (str): Unique key for the slider.
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col (streamlit.columns.Column, optional): Column to place the slider in. Defaults to None (displayed in main area).
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"""
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if col is None:
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@@ -99,30 +109,41 @@ class StateManager:
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@property
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def is_widget_disabled(self):
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return st.session_state['loading_in_progress']
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def disable_widgets(self):
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"""
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Disables widgets by setting the 'loading_in_progress' state to True.
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"""
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st.session_state['loading_in_progress'] = True
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@property
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def settings_changed(self):
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"""
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Checks if any model settings have changed compared to the previous state.
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Returns:
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bool: True if any setting has changed, False otherwise.
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"""
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return self.has_state_changed()
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@property
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def confidance_change(self):
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"""
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Checks if the confidence level setting has changed compared to the previous state.
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@@ -133,9 +154,12 @@ class StateManager:
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return st.session_state["confidence_level"] != st.session_state["previous_state"]["confidence_level"]
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def update_prev_state(self):
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"""
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Updates the 'previous_state' in the session state with the current state values.
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"""
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for key in st.session_state['previous_state']:
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@@ -151,6 +175,9 @@ class StateManager:
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- Sets the detection confidence level on the model object.
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- Updates previous state with current settings for change detection.
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- Updates the button label to "Reload Model".
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"""
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try:
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@@ -166,6 +193,7 @@ 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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def force_reload_model(self) -> None:
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"""
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@@ -175,9 +203,11 @@ class StateManager:
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- Calls `prepare_kbvqa_model` with `force_reload=True` to reload the model.
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- Updates the detection confidence level on the model object.
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- Displays a success message if the model is reloaded successfully.
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"""
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try:
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self.delete_model()
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free_gpu_resources()
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except Exception as e:
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st.error(f"Error reloading model: {e}")
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free_gpu_resources()
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def delete_model(self) -> None:
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"""
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This method deletes the current models and calls `free_gpu_resources`.
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"""
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free_gpu_resources()
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@@ -210,11 +244,10 @@ class StateManager:
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pass
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# Function to check if any session state values have changed
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def has_state_changed(self) -> bool:
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"""
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Compares current session state with the previous state to identify changes.
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Returns:
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bool: True if any change is found, False otherwise.
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"""
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else: return False # No changes found
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def get_model(self) -> KBVQA:
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"""
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Returns:
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"""
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return st.session_state.get('kbvqa', None)
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@property
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def is_model_loaded(self) -> bool:
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"""
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Returns:
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bool: True if the model is loaded, False otherwise.
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"""
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return 'kbvqa' in st.session_state and st.session_state['kbvqa'] is not None and \
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st.session_state.kbvqa.all_models_loaded \
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and (st.session_state['previous_state']['method'] is not None
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- Calls `prepare_kbvqa_model` with `only_reload_detection_model=True`.
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- Updates detection confidence level on the model object.
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- Displays a success message if model is reloaded successfully.
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"""
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try:
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@@ -288,7 +328,9 @@ class StateManager:
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Args:
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image_key (str): Unique key for the image.
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image (obj): The uploaded image data.
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"""
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if image_key not in st.session_state['images_data']:
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'analysis_done': False
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}
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def analyze_image(self, image) -> Tuple[str, str, object]:
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"""
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Args:
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image (obj): The image data to analyze.
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Returns:
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tuple: A tuple containing the generated caption, detected objects string, and image with bounding boxes.
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"""
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def add_to_qa_history(self, image_key: str, question: str, answer: str, prompt_length: int) -> None:
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"""
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Adds a question-answer pair to the QA history of a specific image, to be used as
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Args:
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image_key (str): Unique key for the image.
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question (str): The question asked about the image.
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answer (str): The answer generated by the KBVQA model.
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"""
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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, prompt_length))
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def get_images_data(self):
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"""
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Returns the dictionary containing processed image data from the session state.
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Returns:
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dict: The dictionary storing information about processed images.
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"""
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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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"""
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Updates the information stored for a specific image in the `images_data` dictionary in the application session state.
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caption (str): The generated caption for the image.
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detected_objects_str (str): String representation of detected objects.
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analysis_done (bool): Flag indicating if analysis of the image is complete.
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"""
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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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})
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def resize_image(self, image_input, new_width=None, new_height=None):
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"""
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If both new_width and new_height are provided, the image is resized to those dimensions.
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Args:
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-
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Returns:
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"""
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img = copy.deepcopy(image_input)
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def display_message(self, message, message_type):
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if message_type == "warning":
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st.warning(message)
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elif message_type == "text":
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@property
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def display_model_settings(self):
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"""
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Displays a table of current model settings in the third column.
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"""
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self.col3.write("##### Current Model Settings:")
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data = [{'Setting': 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', 'loading_in_progress', 'model_loaded', 'time_taken_to_load_model', 'images_data' ]]
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return self.col3.write(df)
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def display_session_state(self, col):
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"""
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Displays a table of the complete application state
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"""
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col.write("Current Model:")
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# This module contains the StateManager class.
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# The StateManager class is primarily designed to facilitate the Run Inference tool that allows users to load, run, and test the models.
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import pandas as pd
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import copy
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import time
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from my_model.KBVQA import KBVQA, prepare_kbvqa_model
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class StateManager:
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"""
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Manages the user interface and session state for the Streamlit-based Knowledge-Based Visual Question Answering (KBVQA) application.
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This class includes methods to initialize the session state, set up various UI widgets for model selection and settings,
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manage the loading and reloading of the KBVQA model, and handle the processing and analysis of images.
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It tracks changes to the application's state to ensure the correct configuration is maintained.
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Additionally, it provides methods to display the current model settings and the complete application state within the Streamlit interface.
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The StateManager class is primarily designed to facilitate the Run Inference tool that allows users to load, run, and test the models.
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Attributes:
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col1 (streamlit.columns): The first column in the Streamlit layout.
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col2 (streamlit.columns): The second column in the Streamlit layout.
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col3 (streamlit.columns): The third column in the Streamlit layout.
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"""
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def __init__(self) -> None:
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"""
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Initializes the StateManager instance, setting up the Streamlit columns for the user interface.
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"""
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# Create three columns with different widths
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self.col1, self.col2, self.col3 = st.columns([0.2, 0.6, 0.2])
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def initialize_state(self) -> None:
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"""
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Initializes the Streamlit session state with default values for various keys.
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"""
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if "previous_state" not in st.session_state:
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st.session_state['previous_state'] = {'method': None, 'detection_model': None, 'confidence_level': None}
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if 'images_data' not in st.session_state:
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if 'model_loaded' not in st.session_state:
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st.session_state['model_loaded'] = self.is_model_loaded
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def set_up_widgets(self) -> None:
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"""
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Sets up user interface widgets for selecting models, settings, and displaying model settings conditionally.
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Returns:
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None
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"""
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self.col1.selectbox("Choose a model:", ["13b-Fine-Tuned Model", "7b-Fine-Tuned Model", "Vision-Language Embeddings Alignment"], index=1, key='method', disabled=self.is_widget_disabled)
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self.set_slider_value(text="Select minimum detection confidence level", min_value=0.1, max_value=0.9, value=default_confidence, step=0.05, slider_key_name='confidence_level', col=self.col1)
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# Conditional display of model settings
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show_model_settings = self.col3.checkbox("Show Model Settings", True, disabled=self.is_widget_disabled)
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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: str, min_value: float, max_value: float, value: float, step: float, slider_key_name: str, col=None) -> None:
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"""
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Creates a slider widget with the specified parameters, optionally placing it in a specific column.
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step (float): Step size for the slider.
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slider_key_name (str): Unique key for the slider.
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col (streamlit.columns.Column, optional): Column to place the slider in. Defaults to None (displayed in main area).
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Returns:
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None
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"""
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if col is None:
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@property
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def is_widget_disabled(self) -> bool:
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"""
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Checks if widgets should be disabled based on the 'loading_in_progress' state.
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Returns:
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bool: True if widgets should be disabled, False otherwise.
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"""
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return st.session_state['loading_in_progress']
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def disable_widgets(self) -> None:
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"""
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Disables widgets by setting the 'loading_in_progress' state to True.
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Returns:
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None
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"""
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st.session_state['loading_in_progress'] = True
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@property
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def settings_changed(self) -> bool:
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"""
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Checks if any model settings have changed compared to the previous state.
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Returns:
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bool: True if any setting has changed, False otherwise.
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"""
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return self.has_state_changed()
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@property
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def confidance_change(self) -> bool:
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"""
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Checks if the confidence level setting has changed compared to the previous state.
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return st.session_state["confidence_level"] != st.session_state["previous_state"]["confidence_level"]
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def update_prev_state(self) -> None:
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"""
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Updates the 'previous_state' in the session state with the current state values.
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Returns:
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None
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"""
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for key in st.session_state['previous_state']:
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- Sets the detection confidence level on the model object.
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- Updates previous state with current settings for change detection.
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- Updates the button label to "Reload Model".
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Returns:
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None
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"""
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try:
|
|
|
193 |
|
194 |
except Exception as e:
|
195 |
st.error(f"Error loading model: {e}")
|
196 |
+
|
197 |
|
198 |
def force_reload_model(self) -> None:
|
199 |
"""
|
|
|
203 |
- Calls `prepare_kbvqa_model` with `force_reload=True` to reload the model.
|
204 |
- Updates the detection confidence level on the model object.
|
205 |
- Displays a success message if the model is reloaded successfully.
|
206 |
+
|
207 |
+
Returns:
|
208 |
+
None
|
209 |
"""
|
210 |
|
|
|
211 |
try:
|
212 |
self.delete_model()
|
213 |
free_gpu_resources()
|
|
|
221 |
except Exception as e:
|
222 |
st.error(f"Error reloading model: {e}")
|
223 |
free_gpu_resources()
|
224 |
+
|
225 |
|
226 |
def delete_model(self) -> None:
|
227 |
"""
|
228 |
This method deletes the current models and calls `free_gpu_resources`.
|
229 |
+
|
230 |
+
Returns:
|
231 |
+
None
|
232 |
"""
|
233 |
|
234 |
free_gpu_resources()
|
|
|
244 |
pass
|
245 |
|
246 |
|
|
|
247 |
def has_state_changed(self) -> bool:
|
248 |
"""
|
249 |
Compares current session state with the previous state to identify changes.
|
250 |
+
|
251 |
Returns:
|
252 |
bool: True if any change is found, False otherwise.
|
253 |
"""
|
|
|
260 |
else: return False # No changes found
|
261 |
|
262 |
|
263 |
+
def get_model(self) -> KBVQA.KBVQA():
|
264 |
"""
|
265 |
+
Retrieves the KBVQA model from the session state.
|
266 |
+
|
267 |
+
Returns:
|
268 |
+
KBVQA: The loaded KBVQA model, or None if not loaded.
|
269 |
"""
|
270 |
+
|
271 |
return st.session_state.get('kbvqa', None)
|
272 |
|
273 |
+
|
274 |
@property
|
275 |
def is_model_loaded(self) -> bool:
|
276 |
"""
|
|
|
279 |
Returns:
|
280 |
bool: True if the model is loaded, False otherwise.
|
281 |
"""
|
282 |
+
|
283 |
return 'kbvqa' in st.session_state and st.session_state['kbvqa'] is not None and \
|
284 |
st.session_state.kbvqa.all_models_loaded \
|
285 |
and (st.session_state['previous_state']['method'] is not None
|
|
|
295 |
- Calls `prepare_kbvqa_model` with `only_reload_detection_model=True`.
|
296 |
- Updates detection confidence level on the model object.
|
297 |
- Displays a success message if model is reloaded successfully.
|
298 |
+
|
299 |
+
Returns:
|
300 |
+
None
|
301 |
"""
|
302 |
|
303 |
try:
|
|
|
328 |
Args:
|
329 |
image_key (str): Unique key for the image.
|
330 |
image (obj): The uploaded image data.
|
331 |
+
|
332 |
+
Returns:
|
333 |
+
None
|
334 |
"""
|
335 |
|
336 |
if image_key not in st.session_state['images_data']:
|
|
|
342 |
'analysis_done': False
|
343 |
}
|
344 |
|
345 |
+
|
346 |
|
347 |
def analyze_image(self, image) -> Tuple[str, str, object]:
|
348 |
"""
|
|
|
356 |
Args:
|
357 |
image (obj): The image data to analyze.
|
358 |
|
|
|
359 |
Returns:
|
360 |
tuple: A tuple containing the generated caption, detected objects string, and image with bounding boxes.
|
361 |
"""
|
|
|
371 |
|
372 |
def add_to_qa_history(self, image_key: str, question: str, answer: str, prompt_length: int) -> None:
|
373 |
"""
|
374 |
+
Adds a question-answer pair to the QA history of a specific image, to be used as a history tracker.
|
375 |
|
376 |
Args:
|
377 |
image_key (str): Unique key for the image.
|
378 |
question (str): The question asked about the image.
|
379 |
answer (str): The answer generated by the KBVQA model.
|
380 |
+
prompt_length (int): The length of the prompt used for generating the answer.
|
381 |
+
|
382 |
+
Returns:
|
383 |
+
None
|
384 |
"""
|
385 |
+
|
386 |
if image_key in st.session_state['images_data']:
|
387 |
st.session_state['images_data'][image_key]['qa_history'].append((question, answer, prompt_length))
|
388 |
|
389 |
|
390 |
+
def get_images_data(self) -> Dict:
|
391 |
"""
|
392 |
Returns the dictionary containing processed image data from the session state.
|
393 |
|
394 |
Returns:
|
395 |
dict: The dictionary storing information about processed images.
|
396 |
"""
|
397 |
+
|
398 |
return st.session_state['images_data']
|
399 |
|
400 |
|
401 |
+
def update_image_data(self, image_key: str, caption: str, detected_objects_str: str, analysis_done: bool) -> None:
|
402 |
"""
|
403 |
Updates the information stored for a specific image in the `images_data` dictionary in the application session state.
|
404 |
|
|
|
407 |
caption (str): The generated caption for the image.
|
408 |
detected_objects_str (str): String representation of detected objects.
|
409 |
analysis_done (bool): Flag indicating if analysis of the image is complete.
|
410 |
+
|
411 |
+
Returns:
|
412 |
+
None
|
413 |
"""
|
414 |
if image_key in st.session_state['images_data']:
|
415 |
st.session_state['images_data'][image_key].update({
|
|
|
419 |
})
|
420 |
|
421 |
|
422 |
+
def resize_image(self, image_input, new_width: Optional[int] = None, new_height: Optional[int] = None) -> Image:
|
423 |
"""
|
424 |
+
Resizes an image. If only new_width is provided, the height is adjusted to maintain aspect ratio.
|
425 |
If both new_width and new_height are provided, the image is resized to those dimensions.
|
426 |
|
427 |
Args:
|
428 |
+
image_input (PIL.Image.Image): The image to resize.
|
429 |
+
new_width (int, optional): The target width of the image.
|
430 |
+
new_height (int, optional): The target height of the image.
|
431 |
|
432 |
Returns:
|
433 |
+
PIL.Image.Image: The resized image.
|
434 |
"""
|
435 |
|
436 |
img = copy.deepcopy(image_input)
|
|
|
462 |
|
463 |
|
464 |
|
465 |
+
def display_message(self, message: str, message_type: str) -> None:
|
466 |
+
"""
|
467 |
+
Displays a message in the Streamlit interface based on the specified message type.
|
468 |
+
|
469 |
+
Args:
|
470 |
+
message (str): The message to display.
|
471 |
+
message_type (str): The type of message ('warning', 'text', 'success', 'write', or 'error').
|
472 |
+
|
473 |
+
Returns:
|
474 |
+
None
|
475 |
+
"""
|
476 |
+
|
477 |
if message_type == "warning":
|
478 |
st.warning(message)
|
479 |
elif message_type == "text":
|
|
|
486 |
|
487 |
|
488 |
@property
|
489 |
+
def display_model_settings(self) -> None:
|
490 |
"""
|
491 |
Displays a table of current model settings in the third column.
|
492 |
+
|
493 |
+
Returns:
|
494 |
+
None
|
495 |
"""
|
496 |
self.col3.write("##### Current Model Settings:")
|
497 |
data = [{'Setting': 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', 'loading_in_progress', 'model_loaded', 'time_taken_to_load_model', 'images_data' ]]
|
|
|
499 |
return self.col3.write(df)
|
500 |
|
501 |
|
502 |
+
def display_session_state(self, col) -> None:
|
503 |
"""
|
504 |
+
Displays a table of the complete application state in the specified column.
|
505 |
+
|
506 |
+
Args:
|
507 |
+
col (streamlit.columns.Column): The Streamlit column to display the session state.
|
508 |
+
|
509 |
+
Returns:
|
510 |
+
None
|
511 |
"""
|
512 |
|
513 |
col.write("Current Model:")
|