| """Plotting helpers for tracking statistics.""" |
|
|
| from __future__ import annotations |
|
|
| from pathlib import Path |
|
|
| import matplotlib.pyplot as plt |
| import pandas as pd |
|
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|
|
| def plot_object_counts(frame_df: pd.DataFrame, output_path: str | Path) -> None: |
| """Save a line chart of active tracked objects per frame.""" |
|
|
| if frame_df.empty: |
| return |
|
|
| output_path = Path(output_path) |
| output_path.parent.mkdir(parents=True, exist_ok=True) |
|
|
| plt.figure(figsize=(10, 4)) |
| plt.plot(frame_df["frame"], frame_df["active_tracks"], color="#2364aa", linewidth=2) |
| plt.title("Tracked Object Count Over Time") |
| plt.xlabel("Frame") |
| plt.ylabel("Active Tracks") |
| plt.grid(alpha=0.25) |
| plt.tight_layout() |
| plt.savefig(output_path, dpi=160) |
| plt.close() |
|
|
|
|
| def confidence_histogram(track_df: pd.DataFrame, output_path: str | Path) -> None: |
| """Save a histogram of detection confidence scores.""" |
|
|
| if track_df.empty: |
| return |
|
|
| output_path = Path(output_path) |
| output_path.parent.mkdir(parents=True, exist_ok=True) |
|
|
| plt.figure(figsize=(8, 4)) |
| plt.hist(track_df["confidence"], bins=20, color="#3da35d", edgecolor="white") |
| plt.title("Detection Confidence Distribution") |
| plt.xlabel("Confidence") |
| plt.ylabel("Count") |
| plt.tight_layout() |
| plt.savefig(output_path, dpi=160) |
| plt.close() |
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|
