bria-ai/bria-skill/automotive

Bria Automotive — Vehicle Image Editing & Shot Generation

Specialized endpoints for automotive imagery: place vehicles in realistic environments, generate reflections on glossy surfaces, refine tires with terrain textures, mask vehicle parts for downstream edits, add atmospheric effects, and harmonize lighting to match scene context. Commercially safe, royalty-free, built on Bria's product vehicle pipeline.

When to Use This Skill

Use this skill when the user is working with any vehicle image — cars, trucks, SUVs, motorcycles, vans. Triggers on:

• Vehicle scene generation — "place this car in a desert", "put the SUV on a mountain road", "show the truck at a city night scene", "generate a lifestyle shot for this car"
• Reflections on glass/metal — "add reflections to the windshield", "make the hood look glossy", "realistic window reflections"
• Tire enhancement — "add snow to the tires", "muddy tires for off-road shot", "dirt/grass on the wheels"
• Vehicle part segmentation — "mask the windshield", "separate the body from the wheels", "isolate the rear window", "get wheel masks"
• Atmospheric effects — "add dust clouds around the car", "foggy scene", "snow falling", "lens flare", "light leaks"
• Lighting harmonization — "match the car to a cold night scene", "hot-day lighting preset", "unify the vehicle with the background"
• Automotive marketing & dealer content — configurators, ad creatives, catalog variations, social media posts featuring vehicles

When NOT to Use This Skill

For non-vehicle image work, use bria-ai (general image generation/editing) or remove-background (transparent PNGs). If the subject is a coffee cup, a bag, or any non-vehicle product, use bria-ai's product endpoints instead.

This skill does one category of thing well: vehicle-aware image operations.

Setup — Authentication

Before making any API call, you need a valid Bria access token.

Step 1: Check for existing credentials

if [ -f ~/.bria/credentials ]; then
  BRIA_ACCESS_TOKEN=$(grep '^access_token=' "$HOME/.bria/credentials" | cut -d= -f2-)
  BRIA_API_KEY=$(grep '^api_token=' "$HOME/.bria/credentials" | cut -d= -f2-)
fi
if [ -z "$BRIA_ACCESS_TOKEN" ]; then
  echo "NO_CREDENTIALS"
elif [ -n "$BRIA_API_KEY" ]; then
  echo "READY"
else
  echo "CREDENTIALS_FOUND"
fi

If the output is READY, skip straight to making API calls — no introspection needed. If the output is CREDENTIALS_FOUND, skip to Step 3. If the output is NO_CREDENTIALS, proceed to Step 2.

Step 2: Authenticate via device authorization

2a. Request a device code:

DEVICE_RESPONSE=$(curl -s -X POST "https://engine.prod.bria-api.com/v2/auth/device/authorize" \
  -H "Content-Type: application/json")
echo "$DEVICE_RESPONSE"

Parse the response fields:

• device_code — used to poll for the token (keep this, don't show to user)
• user_code — the code the user must enter (e.g. BRIA-XXXX)
• interval — seconds between poll attempts

2b. Show the user a single sign-in link. Tell them exactly this — nothing more:

Connect your Bria account: Click here to sign in

Your code is {user_code} — it's already filled in.

Do NOT show two links. Do NOT show the raw URL separately. Do NOT use verification_uri from the API response. Keep it to one clickable link.

2c. Poll for the token. After showing the user the code, immediately start polling:

for i in $(seq 1 60); do
  TOKEN_RESPONSE=$(curl -s -X POST "https://engine.prod.bria-api.com/v2/auth/token" \
    -d "grant_type=urn:ietf:params:oauth:grant-type:device_code" \
    -d "device_code=$DEVICE_CODE")
  ACCESS_TOKEN=$(printf '%s' "$TOKEN_RESPONSE" | sed -n 's/.*"access_token" *: *"\([^"]*\)".*/\1/p')
  if [ -n "$ACCESS_TOKEN" ]; then
    BRIA_ACCESS_TOKEN="$ACCESS_TOKEN"
    REFRESH_TOKEN=$(printf '%s' "$TOKEN_RESPONSE" | sed -n 's/.*"refresh_token" *: *"\([^"]*\)".*/\1/p')
    mkdir -p ~/.bria
    printf 'access_token=%s\nrefresh_token=%s\n' "$BRIA_ACCESS_TOKEN" "$REFRESH_TOKEN" > "$HOME/.bria/credentials"
    echo "AUTHENTICATED"
    break
  fi
  sleep 5
done

If the output contains AUTHENTICATED, proceed to Step 3. Otherwise the code expired — start over from Step 2a.

Do not proceed with any API call until authentication is confirmed.

Step 3: Verify billing status and resolve API key

INTROSPECT=$(curl -s -X POST "https://engine.prod.bria-api.com/v2/auth/token/introspect" \
  -d "token=$BRIA_ACCESS_TOKEN")
BILLING_STATUS=$(printf '%s' "$INTROSPECT" | sed -n 's/.*"billing_status" *: *"\([^"]*\)".*/\1/p')
if [ "$BILLING_STATUS" = "blocked" ]; then
  BILLING_MSG=$(printf '%s' "$INTROSPECT" | sed -n 's/.*"billing_message" *: *"\([^"]*\)".*/\1/p')
  echo "BILLING_ERROR: $BILLING_MSG"
fi
ACTIVE=$(printf '%s' "$INTROSPECT" | sed -n 's/.*"active" *: *\([^,}]*\).*/\1/p' | tr -d ' ')
if [ "$ACTIVE" = "false" ]; then
  printf '' > "$HOME/.bria/credentials"
  echo "TOKEN_EXPIRED"
fi
BRIA_API_KEY=$(printf '%s' "$INTROSPECT" | sed -n 's/.*"api_token" *: *"\([^"]*\)".*/\1/p')
if [ -n "$BRIA_API_KEY" ]; then
  grep -v '^api_token=' "$HOME/.bria/credentials" > "$HOME/.bria/credentials.tmp" 2>/dev/null || true
  printf 'api_token=%s\n' "$BRIA_API_KEY" >> "$HOME/.bria/credentials.tmp"
  mv "$HOME/.bria/credentials.tmp" "$HOME/.bria/credentials"
fi

• If BILLING_ERROR: ... — relay the message to the user exactly as shown and stop.
• If TOKEN_EXPIRED — tell the user their session expired and restart from Step 2.
• Otherwise, BRIA_API_KEY is cached. Proceed.

Core Capabilities

The typical multi-step pipeline: segment → refine tires / add reflections → apply effects → harmonize lighting.

How to Call Any Automotive Endpoint

Use bria_call for all API calls. It handles URL passthrough, local file base64 encoding, JSON construction, API call, and async polling in a single function call. The API key is auto-loaded from ~/.bria/credentials.

First, source the helper script at references/code-examples/bria_client.sh (resolve relative to this skill's directory).

source <SKILL_DIR>/references/code-examples/bria_client.sh
 
# Place vehicle in a text-described scene
RESULT=$(bria_call /v1/product/vehicle/shot_by_text "/path/to/car.png" \
  '"scene_description": "coastal highway at sunset, dramatic sky", "placement_type": "automatic", "num_results": 1')
 
# Segment vehicle parts → returns URLs for body, wheels, windows, tires, etc.
RESULT=$(bria_call /v1/product/vehicle/segment "/path/to/car.png")
 
# Add reflections (pairs well with segment output)
RESULT=$(bria_call /v1/product/vehicle/generate_reflections "/path/to/car.png")
 
# Refine tires with snow texture (requires a tire mask)
RESULT=$(bria_call /v1/product/vehicle/refine_tires "/path/to/car.png" \
  --key image \
  '"tire_mask": "https://cdn.example.com/tires_mask.png", "surface": "snow"')
 
# Apply atmospheric dust effect
RESULT=$(bria_call /v1/product/vehicle/apply_effect "/path/to/car.png" \
  '"effect": "dust", "layers": false')
 
# Harmonize to cold-night lighting
RESULT=$(bria_call /v1/product/vehicle/harmonize "/path/to/car.png" \
  '"preset": "cold-night"')
 
echo "$RESULT"

Calling convention: bria_call <endpoint> <image_or_empty> [--key <json_key>] [extra JSON fields...]

• Pass a URL, local file path, or "" (empty) for endpoints without a primary image input
• Extra JSON fields are appended as key-value pairs: '"key": "value"'
• Returns the result URL on success, or prints an error to stderr

See [API Endpoints Reference](references/api-endpoints.md) for the full parameter list, placement options, response schemas, and error codes.

Example Pipelines

Pipeline 1 — Vehicle in a dramatic environment, cold-night look

source <SKILL_DIR>/references/code-examples/bria_client.sh
 
# 1. Place the vehicle in a scene
SCENE_URL=$(bria_call /v1/product/vehicle/shot_by_text "/path/to/car.png" \
  '"scene_description": "empty mountain road with snow flurries", "placement_type": "automatic"')
 
# 2. Harmonize lighting to match a cold night
FINAL_URL=$(bria_call /v1/product/vehicle/harmonize "$SCENE_URL" \
  '"preset": "cold-night"')
 
curl -sL "$FINAL_URL" -o car_cold_night.jpg

Pipeline 2 — Off-road with muddy tires and dust

# 1. Segment tires
MASKS=$(bria_call /v1/product/vehicle/segment "/path/to/car.png")
TIRES_MASK=$(printf '%s' "$MASKS" | sed -n 's/.*"tires" *: *"\([^"]*\)".*/\1/p')
 
# 2. Apply mud surface to tires
MUDDY=$(bria_call /v1/product/vehicle/refine_tires "/path/to/car.png" \
  --key image \
  "\"tire_mask\": \"$TIRES_MASK\", \"surface\": \"mud\"")
 
# 3. Add dust effect
FINAL=$(bria_call /v1/product/vehicle/apply_effect "$MUDDY" \
  '"effect": "dust"')
 
curl -sL "$FINAL" -o offroad.jpg

Pipeline 3 — Glossy showroom shot with studio reflections

# Add reflections on glass and bodywork
SHOWROOM=$(bria_call /v1/product/vehicle/generate_reflections "/path/to/car.png")
 
# Harmonize to bright hot-day lighting
FINAL=$(bria_call /v1/product/vehicle/harmonize "$SHOWROOM" \
  '"preset": "hot-day"')
 
curl -sL "$FINAL" -o showroom.jpg

Placement Types (Vehicle Shot by Text)

See the full list of conditional parameters in API Endpoints Reference.

Prompt Tips for Vehicle Scenes

• Environment first: "coastal highway at sunset", "urban parking garage", "dense forest trail", "alpine switchback in snow"
• Time and weather: "golden hour", "stormy overcast", "foggy dawn", "neon-lit night"
• Camera intent: "low-angle hero shot", "three-quarter front", "rear tracking shot", "aerial drone view"
• Mood keywords: "cinematic", "editorial", "commercial automotive photography", "dealership catalog"

Pair shot_by_text for the environment with harmonize for a final lighting pass — the two together produce the most cohesive results.

Additional Resources

• [API Endpoints Reference](references/api-endpoints.md) — Full parameter docs for all 6 automotive endpoints
• [Shell Client (bria_client.sh)](references/code-examples/bria_client.sh) — bria_call handles auth, base64, JSON, polling
• [Bria automotive docs](https://docs.bria.ai/product-shot-editing/automotive-endpoints) — Upstream reference

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