Python 3 OpenCV & Deep AI Face Recognition & Analysis of Images and Save Result in JSON File

app.py

import json
from deepface import DeepFace
import cv2
import os
import numpy as np  # Add numpy

# Path to image
image_path = "angry.jpg"

# Verify if image exists
if not os.path.exists(image_path):
    print(f"Error: {image_path} not found.")
    exit()

# Load and show the image
img = cv2.imread(image_path)
cv2.imshow("Input Image", img)
cv2.waitKey(1)  # Small delay

# Analyze the face
print("Analyzing face, please wait...")
result = DeepFace.analyze(img_path=image_path, actions=['age', 'gender', 'emotion', 'race'], enforce_detection=False)

# DeepFace returns a list sometimes; pick the first
if isinstance(result, list):
    result = result[0]

# Extract precise information
# Safely convert np.float32 to float
def convert(obj):
    if isinstance(obj, np.float32) or isinstance(obj, np.float64):
        return float(obj)
    return obj

analyzed_info = {
    "Age": convert(result.get('age')),
    "Gender": {k: convert(v) for k, v in result.get('gender', {}).items()},
    "Dominant Emotion": result.get('dominant_emotion'),
    "Dominant Race": result.get('dominant_race')
}

# Display info nicely
print("\nAnalysis Result:")
for key, value in analyzed_info.items():
    print(f"{key}: {value}")

# Save to JSON file
output_file = "analysis_result.json"
with open(output_file, 'w') as f:
    json.dump(analyzed_info, f, indent=4)

print(f"\nAnalysis saved to {output_file}")

# Cleanup
cv2.destroyAllWindows()