import numpy as np import threading import queue from PyQt5.QtWidgets import (QWidget, QVBoxLayout, QHBoxLayout, QLabel, QPushButton, QFrame, QGridLayout) from PyQt5.QtCore import Qt, QThread, pyqtSignal, QTimer from PyQt5.QtGui import QFont, QPalette # Placeholder for matplotlib widget since we'll need it for plotting try: import matplotlib.pyplot as plt from matplotlib.backends.backend_qt5agg import FigureCanvasQTAgg as FigureCanvas from matplotlib.figure import Figure MATPLOTLIB_AVAILABLE = True except ImportError: MATPLOTLIB_AVAILABLE = False class SimilarityThread(QThread): similarity_update = pyqtSignal(float, float) # current_similarity, average_similarity plot_update = pyqtSignal() def __init__(self, motion_app): super().__init__() self.motion_app = motion_app self.is_running = False self.should_stop = False def start_analysis(self): self.is_running = True self.should_stop = False self.start() def stop_analysis(self): self.should_stop = True self.is_running = False def run(self): while self.is_running and not self.should_stop: try: # Get pose data from queue with timeout pose_data = self.motion_app.pose_data_queue.get(timeout=1.0) if pose_data is None: # Poison pill break elapsed_time, standard_angles, webcam_angles = pose_data if standard_angles and webcam_angles: current_similarity = self.motion_app.similarity_analyzer.calculate_similarity( standard_angles, webcam_angles) self.motion_app.similarity_analyzer.add_similarity_score( current_similarity, elapsed_time) # Calculate average history = self.motion_app.similarity_analyzer.similarity_history if history: avg_similarity = sum(history) / len(history) self.similarity_update.emit(current_similarity, avg_similarity) # Emit plot update signal (less frequently) if len(history) % 10 == 0: self.plot_update.emit() self.motion_app.pose_data_queue.task_done() except queue.Empty: continue except Exception as e: continue class SimilarityPlotWidget(QWidget): def __init__(self): super().__init__() self.setup_ui() def setup_ui(self): layout = QVBoxLayout(self) if MATPLOTLIB_AVAILABLE: # Create matplotlib figure self.figure = Figure(figsize=(8, 4)) self.canvas = FigureCanvas(self.figure) layout.addWidget(self.canvas) self.ax = self.figure.add_subplot(111) self.ax.set_title('Similarity Trend') self.ax.set_xlabel('Time (s)') self.ax.set_ylabel('Score (%)') self.ax.set_ylim(0, 100) self.ax.grid(True, alpha=0.3) # Initialize empty line self.line, = self.ax.plot([], [], 'b-', linewidth=2, label='Similarity') self.avg_line = self.ax.axhline(y=0, color='r', linestyle='--', alpha=0.7, label='Average') self.ax.legend() self.figure.tight_layout() self.canvas.draw() else: # Fallback to simple text display self.plot_label = QLabel("matplotlib不可用，无法显示图表") self.plot_label.setAlignment(Qt.AlignCenter) layout.addWidget(self.plot_label) def update_plot(self, timestamps, similarities): if not MATPLOTLIB_AVAILABLE or not timestamps or not similarities: return # Update line data self.line.set_data(timestamps, similarities) # Update average line if similarities: avg = sum(similarities) / len(similarities) self.avg_line.set_ydata([avg, avg]) # Update axis limits if timestamps: self.ax.set_xlim(0, max(timestamps) + 1) self.canvas.draw() class SimilarityDisplayWidget(QWidget): def __init__(self, motion_app): super().__init__() self.motion_app = motion_app self.similarity_thread = SimilarityThread(motion_app) self.setup_ui() self.connect_signals() def setup_ui(self): layout = QVBoxLayout(self) # Title title_label = QLabel("📊 动作相似度分析") title_label.setAlignment(Qt.AlignCenter) title_label.setStyleSheet("font-size: 16pt; font-weight: bold; margin: 10px;") layout.addWidget(title_label) # Metrics display metrics_layout = QGridLayout() # Current similarity self.current_sim_label = QLabel("当前相似度") self.current_sim_value = QLabel("0.0%") self.current_sim_value.setAlignment(Qt.AlignCenter) self.current_sim_value.setStyleSheet("font-size: 24pt; font-weight: bold; color: #0086d3;") # Average similarity self.avg_sim_label = QLabel("平均相似度") self.avg_sim_value = QLabel("0.0%") self.avg_sim_value.setAlignment(Qt.AlignCenter) self.avg_sim_value.setStyleSheet("font-size: 24pt; font-weight: bold; color: #2e7d32;") metrics_layout.addWidget(self.current_sim_label, 0, 0) metrics_layout.addWidget(self.current_sim_value, 1, 0) metrics_layout.addWidget(self.avg_sim_label, 0, 1) metrics_layout.addWidget(self.avg_sim_value, 1, 1) layout.addLayout(metrics_layout) # Plot widget self.plot_widget = SimilarityPlotWidget() layout.addWidget(self.plot_widget) # Final statistics (hidden initially) self.stats_widget = self.create_statistics_widget() self.stats_widget.hide() layout.addWidget(self.stats_widget) def create_statistics_widget(self): stats_widget = QFrame() stats_widget.setFrameStyle(QFrame.StyledPanel) stats_widget.setStyleSheet("background-color: #f0f8ff; border: 1px solid #ccc; border-radius: 5px;") layout = QVBoxLayout(stats_widget) self.final_title = QLabel("🎉 比较完成!") self.final_title.setAlignment(Qt.AlignCenter) self.final_title.setStyleSheet("font-size: 18pt; font-weight: bold; color: #2e7d32; margin: 10px;") self.performance_label = QLabel() self.performance_label.setAlignment(Qt.AlignCenter) self.performance_label.setStyleSheet("font-size: 14pt; font-weight: bold; margin: 5px;") # Final metrics final_metrics_layout = QGridLayout() self.final_avg_label = QLabel("平均相似度") self.final_avg_value = QLabel("0.0%") self.final_max_label = QLabel("最高相似度") self.final_max_value = QLabel("0.0%") self.final_min_label = QLabel("最低相似度") self.final_min_value = QLabel("0.0%") final_metrics_layout.addWidget(self.final_avg_label, 0, 0) final_metrics_layout.addWidget(self.final_avg_value, 1, 0) final_metrics_layout.addWidget(self.final_max_label, 0, 1) final_metrics_layout.addWidget(self.final_max_value, 1, 1) final_metrics_layout.addWidget(self.final_min_label, 0, 2) final_metrics_layout.addWidget(self.final_min_value, 1, 2) layout.addWidget(self.final_title) layout.addWidget(self.performance_label) layout.addLayout(final_metrics_layout) return stats_widget def connect_signals(self): self.similarity_thread.similarity_update.connect(self.update_similarity_display) self.similarity_thread.plot_update.connect(self.update_plot) def start_analysis(self): self.stats_widget.hide() self.motion_app.similarity_analyzer.reset() self.similarity_thread.start_analysis() def stop_analysis(self): self.similarity_thread.stop_analysis() self.show_final_statistics() def update_similarity_display(self, current_similarity, average_similarity): self.current_sim_value.setText(f"{current_similarity:.1f}%") self.avg_sim_value.setText(f"{average_similarity:.1f}%") def update_plot(self): analyzer = self.motion_app.similarity_analyzer if hasattr(analyzer, 'similarity_history') and hasattr(analyzer, 'frame_timestamps'): timestamps = list(analyzer.frame_timestamps) similarities = list(analyzer.similarity_history) self.plot_widget.update_plot(timestamps, similarities) def show_final_statistics(self): history = self.motion_app.similarity_analyzer.similarity_history if not history: return final_avg = sum(history) / len(history) final_max = max(history) final_min = min(history) # Set performance level and color if final_avg >= 80: level = "非常棒! 👏" color = "green" elif final_avg >= 60: level = "整体不错! 👍" color = "blue" else: level = "需要改进! 💪" color = "orange" self.performance_label.setText(f"整体表现: {level}") self.performance_label.setStyleSheet(f"font-size: 14pt; font-weight: bold; margin: 5px; color: {color};") self.final_avg_value.setText(f"{final_avg:.1f}%") self.final_max_value.setText(f"{final_max:.1f}%") self.final_min_value.setText(f"{final_min:.1f}%") self.stats_widget.show()