env.example

# Camera settings. Copy this file to `.env`, then calibrate your camera:
#
#   cp .env.example .env
#   uv run python testdata/verify_scores.py
#
# The defaults were measured with an Arducam 1080P at 1280x720 on a desk.
# A different camera, distance, or lighting will change the scores. See
# docs/calibration.md for help reading the calibration results.

# --- recognition ------------------------------------------------------------

# The minimum similarity score needed to recognize a taught object.
# Unrelated images from the same camera often score between 0.75 and 0.85, so
# 0.90 does not mean "90% confident." verify_scores.py helps find this value.
# Too low: everything in the room matches the last thing you taught.
# Too high: the object stops being recognized when it turns or the light shifts.
RECOGNIZE_THRESHOLD=0.90

# --- detection --------------------------------------------------------------

# Raise this value to track less clutter. Lower it to detect more objects.
DETECT_CONF=0.30

# Largest detection kept, as a fraction of the frame. This removes boxes around
# walls, desks, and other areas that are too large to teach. Raise it if the
# objects you want to teach are large in the frame.
DETECT_MAX_AREA=0.20

# Smallest detection kept, as a fraction of the frame. Raise it if distant
# clutter draws attention away from the object you are teaching.
# This setting measures area. Doubling it makes the smallest tracked object
# about 40% wider, not twice as wide.
DETECT_MIN_AREA=0.001

# --- camera -----------------------------------------------------------------

# Set this to 0 for an upright camera or 180 for an upside-down camera. The
# camera is upside down when mounted in the robot. Set this before teaching
# anything because CLIP does not ignore image rotation. If you change it later,
# you will need to teach the objects again. Only 0 and 180 are supported; the
# app expects a landscape image.
CAMERA_ROTATE=0

# Crop unwanted edges from the camera image. Use one fraction for every edge,
# or four values in left,top,right,bottom order. This is useful when a wide lens
# leaves a black rim in the frame. The crop is applied after CAMERA_ROTATE, so
# `top` means the top of the image shown in the app. To measure the crop, hold
# a white card against the lens, capture a frame, and crop away the unlit edges.
FRAME_CROP=0

# --- microphone -------------------------------------------------------------

# Leave this unset to use the system's default microphone. If the wrong input
# opens, set a device name or numeric index from:
#   uv run python -c "import sounddevice; print(sounddevice.query_devices())"
# MIC_DEVICE=1