Update visualization.py

visualization.py

@@ -7,7 +7,7 @@ from utils import seconds_to_timecode
 from anomaly_detection import determine_anomalies
 
 def plot_mse(df, mse_values, title, color='navy', time_threshold=3, anomaly_threshold=4):
-    plt.figure(figsize=(16, 8), dpi=400)
+    plt.figure(figsize=(16, 8), dpi=300)
     fig, ax = plt.subplots(figsize=(16, 8))
 
     if 'Seconds' not in df.columns:
@@ -117,7 +117,7 @@ def plot_mse(df, mse_values, title, color='navy', time_threshold=3, anomaly_thre
     return fig, anomaly_frames
 
 def plot_mse_histogram(mse_values, title, anomaly_threshold, color='blue'):
-    plt.figure(figsize=(16, 3), dpi=400)
+    plt.figure(figsize=(16, 3), dpi=300)
     fig, ax = plt.subplots(figsize=(16, 3))
 
     ax.hist(mse_values, bins=100, edgecolor='black', color=color, alpha=0.7)
@@ -136,7 +136,7 @@ def plot_mse_histogram(mse_values, title, anomaly_threshold, color='blue'):
     return fig
 
 def plot_mse_heatmap(mse_values, title, df):
-    plt.figure(figsize=(20, 3), dpi=400)
+    plt.figure(figsize=(20, 3), dpi=300)
     fig, ax = plt.subplots(figsize=(20, 3))
 
     # Reshape MSE values to 2D array for heatmap
@@ -163,7 +163,7 @@ def plot_mse_heatmap(mse_values, title, df):
     return fig
 
 def plot_posture(df, posture_scores, color='blue', anomaly_threshold=3):
-    plt.figure(figsize=(16, 8), dpi=400)
+    plt.figure(figsize=(16, 8), dpi=300)
     fig, ax = plt.subplots(figsize=(16, 8))
 
     df['Seconds'] = df['Timecode'].apply(