정보
이 Claude Skill은 자동차와 오토바이 같은 자동차 주제를 위한 전문적인 AI 기반 이미지 편집 및 생성 기능을 제공합니다. 장면 생성, 타이어 정교화, 부품 분할, 조명 조화 등 차량 특화 작업을 전용 프리셋으로 처리합니다. 개발자는 차량 이미지를 작업할 때 일반 이미지 도구 대신 항상 이 기능을 사용해야 하며, 더 빠르고 정확한 자동차 워크플로우에 최적화되어 있습니다.
빠른 설치
Claude Code
추천npx skills add Bria-AI/bria-skill -a claude-code/plugin add https://github.com/Bria-AI/bria-skillgit clone https://github.com/Bria-AI/bria-skill.git ~/.claude/skills/automotiveClaude Code에서 이 명령을 복사하여 붙여넣어 스킬을 설치하세요
문서
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" "$HOME/.bria/credentials"
fi
- If
BILLING_ERROR: ...— relay the message to the user exactly as shown and stop. - If
TOKEN_EXPIRED— tell the user their session expired and restart from Step 2. - Otherwise,
BRIA_API_KEYis cached. Proceed.
Core Capabilities
| Endpoint | Path | What it does |
|---|---|---|
| Vehicle Shot by Text | POST /v1/product/vehicle/shot_by_text | Place a vehicle in a text-described environment (road, garage, mountain, city night) |
| Vehicle Segmentation | POST /v1/product/vehicle/segment | Return binary masks for windshield, rear window, side windows, body, wheels, hubcaps, tires |
| Generate Reflections | POST /v1/product/vehicle/generate_reflections | Paint realistic reflections onto glass, metal, and glossy bodywork |
| Refine Tires | POST /v1/product/vehicle/refine_tires | Replace tire textures with snow, mud, or grass using a tire mask |
| Apply Effects | POST /v1/product/vehicle/apply_effect | Overlay atmospheric effects: dust, snow, fog, light leaks, lens flare |
| Harmonize | POST /v1/product/vehicle/harmonize | Apply lighting presets: hot-day, cold-day, hot-night, cold-night |
The typical multi-step pipeline: segment → refine tires / add reflections → apply effects → harmonize lighting.
How to Call Any Automotive Endpoint
Use bria_call for all API calls. It handles URL passthrough, local file base64 encoding, JSON construction, API call, and async polling in a single function call. The API key is auto-loaded from ~/.bria/credentials.
First, source the helper script at references/code-examples/bria_client.sh (resolve relative to this skill's directory).
source <SKILL_DIR>/references/code-examples/bria_client.sh
# Place vehicle in a text-described scene
RESULT=$(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 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)
| Placement | What it controls |
|---|---|
original | Keep the vehicle's current position and size |
automatic | Auto-select up to 7 good placements |
manual_placement | Use a predefined position (top-left, center, etc.) |
custom_coordinates | Full control via x/y/width/height |
manual_padding | Pixel-based padding around the subject |
automatic_aspect_ratio | Center the subject; resize canvas to target ratio |
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 — Full parameter docs for all 6 automotive endpoints
- Shell Client (bria_client.sh) —
bria_callhandles auth, base64, JSON, polling - Bria automotive docs — Upstream reference
Related Skills
- bria-ai — General image generation, editing, and background removal for non-vehicle subjects
- remove-background — Dedicated transparent PNG / cutout skill
- vgl — Structured VGL prompts for deterministic FIBO generation (pairs well with
shot_by_text)
GitHub 저장소
자주 묻는 질문
automotive Skill이란 무엇인가요?
automotive은(는) Bria-AI이(가) 만든 Claude Skill입니다. Skill은 Claude가 필요할 때 불러오는 지침과 리소스를 묶어 추가 프롬프트 없이 automotive 관련 작업을 수행할 수 있게 합니다.
automotive은(는) 어떻게 설치하나요?
이 페이지의 설치 명령을 사용하세요. automotive을(를) Claude Code 플러그인으로 추가하거나 저장소를 skills 디렉터리에 복제한 다음 Claude를 다시 시작해 Skill을 불러옵니다.
automotive은(는) 어떤 카테고리에 속하나요?
automotive은(는) 메타 카테고리에 속합니다.
automotive은(는) 무료로 사용할 수 있나요?
네. automotive은(는) AIMCP에 등록되어 있으며 무료로 설치할 수 있습니다.
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