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| import pandas as pd | |
| import copy | |
| import streamlit as st | |
| from my_model.gen_utilities import free_gpu_resources | |
| from my_model.KBVQA import KBVQA, prepare_kbvqa_model | |
| class StateManager: | |
| def __init__(self): | |
| self.initialize_state() | |
| def initialize_state(self): | |
| if 'images_data' not in st.session_state: | |
| st.session_state['images_data'] = {} | |
| if 'model_settings' not in st.session_state: | |
| st.session_state['model_settings'] = {'detection_model': None, 'confidence_level': None} | |
| if 'kbvqa' not in st.session_state: | |
| st.session_state['kbvqa'] = None | |
| if 'selected_method' not in st.session_state: | |
| st.session_state['selected_method'] = None | |
| def update_model_settings(self, detection_model=None, confidence_level=None, selected_method=None): | |
| if detection_model is not None: | |
| st.session_state['model_settings']['detection_model'] = detection_model | |
| if confidence_level is not None: | |
| st.session_state['model_settings']['confidence_level'] = confidence_level | |
| if selected_method is not None: | |
| st.session_state['selected_method'] = selected_method | |
| def check_settings_changed(self, current_selected_method, current_detection_model, current_confidence_level): | |
| return (st.session_state['model_settings']['detection_model'] != current_detection_model or | |
| st.session_state['model_settings']['confidence_level'] != current_confidence_level or | |
| st.session_state['selected_method'] != current_selected_method) | |
| def display_model_settings(self): | |
| st.write("### Current Model Settings:") | |
| st.table(pd.DataFrame(st.session_state['model_settings'], index=[0])) | |
| def display_session_state(self): | |
| st.write("### Current Session State:") | |
| data = [{'Key': key, 'Value': str(value)} for key, value in st.session_state.items()] | |
| df = pd.DataFrame(data) | |
| st.table(df) | |
| def load_model(self, detection_model, confidence_level): | |
| """Load the KBVQA model with specified settings.""" | |
| try: | |
| free_gpu_resources() | |
| st.text("Loading the model, please wait...") | |
| st.session_state['kbvqa'] = prepare_kbvqa_model(detection_model) | |
| st.session_state['kbvqa'].detection_confidence = confidence_level | |
| self.update_model_settings(detection_model, confidence_level) | |
| st.write("Model is ready for inference.") | |
| free_gpu_resources() | |
| except Exception as e: | |
| st.error(f"Error loading model: {e}") | |
| def get_model(self): | |
| """Retrieve the KBVQA model from the session state.""" | |
| return st.session_state.get('kbvqa', None) | |
| def is_model_loaded(self): | |
| return 'kbvqa' in st.session_state and st.session_state['kbvqa'] is not None | |
| def reload_detection_model(self, detection_model, confidence_level): | |
| try: | |
| free_gpu_resources() | |
| if self.is_model_loaded(): | |
| prepare_kbvqa_model(detection_model, only_reload_detection_model=True) | |
| st.session_state['kbvqa'].detection_confidence = confidence_level | |
| self.update_model_settings(detection_model, confidence_level) | |
| free_gpu_resources() | |
| except Exception as e: | |
| st.error(f"Error reloading detection model: {e}") | |
| # New methods to be added | |
| def process_new_image(self, image_key, image, kbvqa): | |
| 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 analyze_image(self, image, kbvqa): | |
| img = copy.deepcopy(image) | |
| caption = kbvqa.get_caption(img) | |
| image_with_boxes, detected_objects_str = kbvqa.detect_objects(img) | |
| return caption, detected_objects_str, image_with_boxes | |
| def add_to_qa_history(self, image_key, question, answer): | |
| if image_key in st.session_state['images_data']: | |
| st.session_state['images_data'][image_key]['qa_history'].append((question, answer)) | |
| def get_images_data(self): | |
| return st.session_state['images_data'] | |
| def update_image_data(self, image_key, caption, detected_objects_str, analysis_done): | |
| if image_key in st.session_state['images_data']: | |
| st.session_state['images_data'][image_key].update({ | |
| 'caption': caption, | |
| 'detected_objects_str': detected_objects_str, | |
| 'analysis_done': analysis_done | |
| }) | |