Roboflow Workflows로 시선 감지와 추적 파이프라인 구축하기

import os
from inference_sdk import InferenceHTTPClient
from inference_sdk.webrtc import VideoFileSource, StreamConfig, VideoMetadata

client = InferenceHTTPClient.init(
    api_url="https://serverless.roboflow.com",
    api_key=os.getenv("ROBOFLOW_API_KEY")
)

# WebRTC stream configuration
config = StreamConfig(
    stream_output=[],
    data_output=[
        "output_image",              # Frame with bounding boxes visualized
        "stabilized_predictions"     # Stabilized face predictions with tracker IDs
    ],
    requested_plan="webrtc-gpu-medium",
    requested_region="us"
)

INPUT_VIDEO = "input.mp4"
source = VideoFileSource(INPUT_VIDEO, realtime_processing=False)

# Start WebRTC session
session = client.webrtc.stream(
    source=source,
    workflow="human-face-detection-1788782690880",
    workspace="dikshants-blog-workspace",
    image_input="image",
    config=config
)

# Run workflow
session.run()

import json

# Save face predictions for entire video to JSON
FACE_PREDICTIONS_JSON = "face_predictions.json"
with open(FACE_PREDICTIONS_JSON, "w", encoding="utf-8") as f:
    json.dump(face_predictions_by_frame, f, indent=2)

print("Roboflow processing completed.")

# Gaze tracking configuration
GAZE_SMOOTHING_ALPHA = 0.18
FACE_CENTER_SMOOTHING_ALPHA = 0.30

# Smoothing function for gaze and face center values
def smooth_value(previous, current, alpha):
    if previous is None:
        return current
    return alpha * current + (1.0 - alpha) * previous