example.env

# InsightFace-REST Configuration
# ==============================

# Docker Compose project name (used for container naming)
COMPOSE_PROJECT_NAME=insightface-rest

# InsightFace-REST Docker image version
IFR_VERSION=v0.9.5.0

# Face Detection Model (choose from: retinaface*, scrfd*, yolov5*-face, centerface)
# Note: SCRFD models require input dimensions divisible by 32 (e.g., 640x640)
DET_NAME=retinaface_r50_v1

# Face Recognition Model (choose from: arcface*, glintr100, w600k*, adaface*)
REC_NAME=w600k_r50

# Gender/Age Model (None to disable, or 'genderage_v1')
GA_MODEL=None

# Face Mask Detection Model (None to disable, or 'mask_detector*')
MASK_DETECTOR=None

# Batch Processing Configuration
# ------------------------------
# Recognition batch size (higher = better throughput but more GPU memory)
REC_BATCH_SIZE=64
# Detection batch size (requires batch-supported detectors like SCRFD/YOLOv5)
DET_BATCH_SIZE=8

# Default Request Parameters
# --------------------------
# Face detection confidence threshold (0.0-1.0)
DEF_DET_THRESH=0.6
# Return base64-encoded face crops in responses
DEF_RETURN_FACE_DATA=False
# Enable gender/age estimation in responses
DEF_EXTRACT_GA=False
# Return face embeddings/feature vectors in responses
DEF_EXTRACT_EMBEDDING=True
# HTTP headers for image URL fetching (i.e. user agent to prevent blocking, or authorization headers)
DEF_IMG_REQ_HEADERS='{"User-Agent": "Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:126.0) Gecko/20100101 Firefox/126.0"}'

# Performance Settings
# --------------------
# Maximum input image dimensions (W,H) - smaller=faster
# Note: SCRFD models require input dimensions divisible by 32 (e.g., 640x640)
MAX_SIZE=640,640
# Inference backend (trt=TensorRT, onnx=ONNX Runtime)
INFERENCE_BACKEND=trt
# Force FP16 mode for TensorRT (boosts speed on compatible GPUs)
FORCE_FP16=True
# Worker processes per container (higher=better concurrency)
NUM_WORKERS=1

# System Configuration
# --------------------
# Log verbosity (DEBUG, INFO, WARNING, ERROR)
LOG_LEVEL=INFO
# Use GPU-accelerated JPEG decoding (requires compatible GPU)
USE_NVJPEG=False

# Advanced
# --------
# Face model implementation class (custom implementations)
FACE_MODEL_CLASS=face_model