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import pandas as pd
import matplotlib.pyplot as plt
from persistence import load_detection_data
import argparse
def visualize_detections(json_path):
"""
Visualize detection data from a JSON file.
Args:
json_path (str): Path to the JSON file containing detection data.
"""
# Load the persisted JSON data
data = load_detection_data(json_path)
if not data:
return
# Convert the frame detections to a DataFrame
rows = []
for frame_data in data["frame_detections"]:
frame = frame_data["frame"]
timestamp = frame_data["timestamp"]
for obj in frame_data["objects"]:
rows.append({
"frame": frame,
"timestamp": timestamp,
"keyword": obj["keyword"],
"x1": obj["bbox"][0],
"y1": obj["bbox"][1],
"x2": obj["bbox"][2],
"y2": obj["bbox"][3],
"area": (obj["bbox"][2] - obj["bbox"][0]) * (obj["bbox"][3] - obj["bbox"][1])
})
if not rows:
print("No detections found in the data")
return
df = pd.DataFrame(rows)
# Create a figure with multiple subplots
fig = plt.figure(figsize=(15, 10))
# Plot 1: Number of detections per frame
plt.subplot(2, 2, 1)
detections_per_frame = df.groupby("frame").size()
plt.plot(detections_per_frame.index, detections_per_frame.values)
plt.xlabel("Frame")
plt.ylabel("Number of Detections")
plt.title("Detections Per Frame")
# Plot 2: Distribution of detection areas
plt.subplot(2, 2, 2)
df["area"].hist(bins=30)
plt.xlabel("Detection Area (normalized)")
plt.ylabel("Count")
plt.title("Distribution of Detection Areas")
# Plot 3: Average detection area over time
plt.subplot(2, 2, 3)
avg_area = df.groupby("frame")["area"].mean()
plt.plot(avg_area.index, avg_area.values)
plt.xlabel("Frame")
plt.ylabel("Average Detection Area")
plt.title("Average Detection Area Over Time")
# Plot 4: Heatmap of detection centers
plt.subplot(2, 2, 4)
df["center_x"] = (df["x1"] + df["x2"]) / 2
df["center_y"] = (df["y1"] + df["y2"]) / 2
plt.hist2d(df["center_x"], df["center_y"], bins=30)
plt.colorbar()
plt.xlabel("X Position")
plt.ylabel("Y Position")
plt.title("Detection Center Heatmap")
# Adjust layout and display
plt.tight_layout()
plt.show()
# Print summary statistics
print("\nSummary Statistics:")
print(f"Total frames analyzed: {len(data['frame_detections'])}")
print(f"Total detections: {len(df)}")
print(f"Average detections per frame: {len(df) / len(data['frame_detections']):.2f}")
print(f"\nVideo metadata:")
for key, value in data["video_metadata"].items():
print(f"{key}: {value}")
def main():
parser = argparse.ArgumentParser(description="Visualize object detection data")
parser.add_argument("json_file", help="Path to the JSON file containing detection data")
args = parser.parse_args()
visualize_detections(args.json_file)
if __name__ == "__main__":
main() |