automotive
Vehicle/automotive image editing for cars, trucks, SUVs, motorcycles — car scenes, reflections, tires refinement with snow/mud/grass, segment windshield/wheels/body/windows/hubcaps, atmospheric effects (dust, fog, snow, light leaks, lens flare), and lighting harmonization (hot-da
Install
npx skills add https://github.com/Bria-AI/bria-skill/tree/main/bria-ai-openclaw/skills/automotive
claude plugin marketplace add https://llmmart.ai/marketplace.json && claude plugin install bria-ai-bria-skill@llmmart
git clone https://github.com/Bria-AI/bria-skill.git
The skills CLI installs just this skill, for any of its supported agents. Claude Code installs the whole bria-ai/bria-skill collection as a plugin from our marketplace. Git is the plain clone.
Skill manifest
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 — 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)
Files (bria-skill)
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references
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code-examples
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bria_client.sh 4.1 KB
#!/bin/bash # bria_client.sh — Self-contained helper for Bria API calls. # Zero dependencies beyond curl, base64, sed (standard on macOS/Linux). # # Usage: # source bria_client.sh # RESULT=$(bria_call /v2/image/generate "" '"prompt":"a sunset","aspect_ratio":"16:9","sync":true') # RESULT=$(bria_call /v2/image/edit/remove_background "/path/to/image.png") # RESULT=$(bria_call /v2/image/edit/replace_background "https://example.com/img.jpg" '"prompt":"sunset beach"') # RESULT=$(bria_call /v2/image/edit "/path/to/image.png" --key images '"instruction":"make it red"') # # BRIA_API_KEY is auto-loaded from ~/.bria/credentials if not already set. BRIA_API_BASE="${BRIA_API_BASE:-https://engine.prod.bria-api.com}" BRIA_USER_AGENT="BriaSkills/1.3.7" bria_call() { local endpoint image key extra payload result http_code body url status_url poll i endpoint="$1"; image="$2"; shift 2 key="image"; extra="" while [ $# -gt 0 ]; do case "$1" in --key) key="$2"; shift 2 ;; *) extra="${extra:+$extra, }$1"; shift ;; esac done if [ -z "$BRIA_API_KEY" ] && [ -f "$HOME/.bria/credentials" ]; then BRIA_API_KEY=$(grep '^api_token=' "$HOME/.bria/credentials" | cut -d= -f2-) fi [ -z "$BRIA_API_KEY" ] && { echo "ERROR: BRIA_API_KEY not set. Run auth first." >&2; return 1; } # --- Build JSON payload to temp file (safe for large images) --- payload="/tmp/bria_payload_$$.json" if [ -z "$image" ]; then printf '{' > "$payload" elif printf '%s' "$image" | grep -qE '^https?://'; then if [ "$key" = "images" ]; then printf '{"images": ["%s"]' "$image" > "$payload" else printf '{"%s": "%s"' "$key" "$image" > "$payload" fi else [ ! -f "$image" ] && { echo "ERROR: File not found: $image" >&2; return 1; } if [ "$key" = "images" ]; then printf '{"images": ["' > "$payload" else printf '{"%s": "' "$key" > "$payload" fi base64 < "$image" | tr -d '\n' >> "$payload" if [ "$key" = "images" ]; then printf '"]' >> "$payload" else printf '"' >> "$payload" fi fi if [ -n "$extra" ]; then if [ -z "$image" ]; then printf '%s' "$extra" >> "$payload" else printf ', %s' "$extra" >> "$payload" fi fi printf '}' >> "$payload" # --- API call --- result="/tmp/bria_result_$$.json" http_code=$(curl -s -o "$result" -w '%{http_code}' -X POST \ "${BRIA_API_BASE}${endpoint}" \ -H "api_token: $BRIA_API_KEY" \ -H "Content-Type: application/json" \ -H "User-Agent: $BRIA_USER_AGENT" \ -d @"$payload") body=$(cat "$result") rm -f "$payload" "$result" # --- Error handling --- case "$http_code" in 401) echo "ERROR 401: API key invalid. Delete ~/.bria/credentials and re-authenticate." >&2; return 1 ;; 403) echo "ERROR 403: Billing/quota issue. Visit https://platform.bria.ai/pricing" >&2; echo "$body" >&2; return 1 ;; 5*) echo "ERROR $http_code: Server error. Try again shortly." >&2; return 1 ;; esac if [ "${http_code:-0}" -ge 400 ] 2>/dev/null; then echo "ERROR $http_code: $body" >&2; return 1 fi # --- Extract result URL (sync response) --- url=$(printf '%s' "$body" | sed -n 's/.*"result_url" *: *"\([^"]*\)".*/\1/p') [ -n "$url" ] && { echo "$url"; return 0; } url=$(printf '%s' "$body" | sed -n 's/.*"image_url" *: *"\([^"]*\)".*/\1/p') [ -n "$url" ] && { echo "$url"; return 0; } # --- Async: poll status_url --- status_url=$(printf '%s' "$body" | sed -n 's/.*"status_url" *: *"\([^"]*\)".*/\1/p') if [ -n "$status_url" ]; then i=0 while [ "$i" -lt 30 ]; do sleep 3 poll=$(curl -s "$status_url" \ -H "api_token: $BRIA_API_KEY" \ -H "User-Agent: $BRIA_USER_AGENT") if printf '%s' "$poll" | grep -qE '"status" *: *"(ERROR|FAILED)"'; then echo "ERROR: Job failed. Response: $poll" >&2; return 1 fi url=$(printf '%s' "$poll" | sed -n 's/.*"result_url" *: *"\([^"]*\)".*/\1/p') [ -z "$url" ] && url=$(printf '%s' "$poll" | sed -n 's/.*"image_url" *: *"\([^"]*\)".*/\1/p') [ -n "$url" ] && { echo "$url"; return 0; } i=$((i + 1)) done echo "ERROR: Polling timed out after 90 seconds" >&2 return 1 fi echo "$body" }
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api-endpoints.md 7.5 KB
# Bria.ai Automotive API Reference ## Base URL & Authentication **Base URL:** `https://engine.prod.bria-api.com` **Authentication:** Include these headers in all requests: ``` api_token: YOUR_BRIA_API_KEY Content-Type: application/json User-Agent: BriaSkills/<version> ``` > All automotive endpoints live under the `/v1/product/vehicle/*` namespace. Each endpoint accepts either an `image_url` OR a base64-encoded `file`. When both are provided, `image_url` takes precedence. --- ## POST /v1/product/vehicle/shot_by_text Place a vehicle into a realistic, text-described environment. Produces enriched automotive shots by embedding the vehicle into the scene for a natural, grounded appearance. **Parameters:** | Parameter | Type | Required | Default | Description | |-----------|------|----------|---------|-------------| | `image_url` | string | one of image_url/file | — | Vehicle image URL (jpeg, jpg, png, webp; max 12MB) | | `file` | string | one of image_url/file | — | Base64-encoded vehicle image | | `scene_description` | string | yes | — | Text description of the desired environment | | `placement_type` | string | yes | — | See "Placement Types" below | | `shot_size` | object | conditional | — | Output image dimensions (depends on placement_type) | | `manual_placement_selection` | string | when `manual_placement` | — | Predefined position name | | `foreground_image_size` | object | when `custom_coordinates` | — | Vehicle size inside the frame | | `foreground_image_location` | object | when `custom_coordinates` | — | Vehicle x/y origin | | `manual_padding` | number | when `manual_padding` | — | Padding in pixels around the vehicle | | `aspect_ratio` | string | when `automatic_aspect_ratio` | — | Target canvas aspect ratio | | `num_results` | number | no | 1 | Number of variations (up to 7 in `automatic` mode) | ### Placement Types | Placement | Behavior | |-----------|----------| | `original` | Preserves original vehicle position and size | | `automatic` | Returns up to 7 recommended placements | | `manual_placement` | Uses a predefined position | | `custom_coordinates` | Full control via `foreground_image_size` + `foreground_image_location` | | `manual_padding` | Adds pixel padding around the vehicle | | `automatic_aspect_ratio` | Centers the vehicle and resizes the canvas to `aspect_ratio` | **Request example:** ```json { "image_url": "https://example.com/car.png", "scene_description": "winding alpine road, golden hour lighting", "placement_type": "automatic", "num_results": 3 } ``` **Response:** Returns URLs of the enriched automotive shots with the vehicle embedded in the generated scene. --- ## POST /v1/product/vehicle/segment Generate binary segmentation masks for specific vehicle parts. Each returned field is either a PNG mask URL or an empty string when the part is not visible. Masks power downstream edits such as reflection generation or tire refinement. **Parameters:** | Parameter | Type | Required | Description | |-----------|------|----------|-------------| | `image_url` | string | one of image_url/file | Vehicle image URL (jpeg, jpg, png, webp; max 12MB) | | `file` | string | one of image_url/file | Base64-encoded image | **Response schema:** | Field | Type | Description | |-------|------|-------------| | `windshield` | string | Front windshield mask URL | | `rear_window` | string | Rear window mask URL | | `side_windows` | string | All visible side windows combined | | `body` | string | Vehicle body (painted surfaces) | | `wheels` | string | All visible wheels | | `hubcap` | string | All visible hubcaps | | `tires` | string | All visible tires (use as input to `refine_tires`) | --- ## POST /v1/product/vehicle/generate_reflections Paint realistic reflections onto glossy surfaces such as windshields, side windows, and painted bodywork. Reflection masks may be supplied manually or generated automatically with the segmentation endpoint. **Parameters:** | Parameter | Type | Required | Description | |-----------|------|----------|-------------| | `image_url` | string | one of image_url/file | Vehicle image URL | | `file` | string | one of image_url/file | Base64-encoded image | | `masks` | object | no | Optional per-region reflection masks | | `layers` | boolean | no | When true, also returns per-region reflection layers | **Response:** Updated vehicle image with applied reflections, plus optional reflection layers per region. --- ## POST /v1/product/vehicle/refine_tires Replace tire textures with a realistic terrain surface. Requires a tire mask (use `/v1/product/vehicle/segment` first to obtain one automatically). **Parameters:** | Parameter | Type | Required | Default | Description | |-----------|------|----------|---------|-------------| | `image` | string | yes | — | Vehicle image (URL or base64) | | `tire_mask` | string | yes | — | Binary mask of all tires (URL or base64) | | `surface` | string | yes | — | One of `snow`, `mud`, `grass` | | `output_tire_layer` | boolean | no | `false` | When true, also returns just the refined tires layer | **Response schema:** ```json { "image": "https://…/vehicle_with_refined_tires.jpg", "tire_layer": "https://…/tire_layer.png" } ``` --- ## POST /v1/product/vehicle/apply_effect Apply atmospheric overlays to a vehicle image for added realism or dramatic mood. **Parameters:** | Parameter | Type | Required | Default | Description | |-----------|------|----------|---------|-------------| | `image_url` | string | one of image_url/file | — | Vehicle image URL | | `file` | string | one of image_url/file | — | Base64-encoded vehicle image | | `effect` | string | yes | — | One of `dust`, `snow`, `fog`, `light leaks`, `lens flare` | | `layers` | boolean | no | `false` | When true, returns only the effect layer; when false, returns the composited image | | `seed` | integer | no | random | Seed for reproducible effect variations | **Request example:** ```json { "image_url": "https://example.com/car.jpg", "effect": "fog", "layers": false, "seed": 12345 } ``` **Response schema:** ```json { "url": "https://.../car_fog.jpg", "layer_url": "https://.../fog_layer.png", "seed": 12345 } ``` `layer_url` is returned only when `layers=true`. --- ## POST /v1/product/vehicle/harmonize Apply a predefined lighting and tone preset so the vehicle visually matches a desired environmental context (useful after `shot_by_text`). **Parameters:** | Parameter | Type | Required | Description | |-----------|------|----------|-------------| | `image_url` | string | one of image_url/file | Vehicle image URL | | `file` | string | one of image_url/file | Base64-encoded vehicle image | | `preset` | string | yes | One of `hot-day`, `cold-day`, `hot-night`, `cold-night` | **Response:** Updated image with harmonized lighting/tone; the vehicle subject is unified with its background for visual consistency. --- ## Error Handling All automotive endpoints may return the following HTTP status codes: | Code | Meaning | |------|---------| | 400 | Bad request — malformed parameters | | 401 | Unauthorized — invalid or missing `api_token` | | 404 | Resource not found | | 413 | Payload too large (>12MB) | | 415 | Unsupported image format | | 422 | Semantic validation failed (e.g. missing required mask) | | 429 | Rate limit exceeded | | 460 | Content moderation blocked the input or output | | 500 | Server error | ### Supported Image Formats JPEG, PNG, WEBP — up to 12MB per image. ### Content Moderation All automotive endpoints support an optional content moderation flag that filters unsafe inputs and outputs. Refer to the upstream docs for the parameter name per endpoint.
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LICENSE.txt 1.3 KB
MIT License Copyright (c) 2025 Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. --- Note: This skill integrates with Bria.ai's API. Usage of the Bria.ai API is subject to Bria.ai's Terms of Service and API usage policies. The Bria.ai API and associated models are commercial products - please refer to https://bria.ai for licensing and pricing information. -
SKILL.md 12.7 KB
--- name: automotive description: Vehicle/automotive image editing for cars, trucks, SUVs, motorcycles — car scenes, reflections, tires refinement with snow/mud/grass, segment windshield/wheels/body/windows/hubcaps, atmospheric effects (dust, fog, snow, light leaks, lens flare), and lighting harmonization (hot-day, cold-day, hot-night, cold-night presets). Powered by Bria.ai's dedicated automotive pipeline. Use this skill whenever the user mentions a car, vehicle, truck, SUV, motorcycle, auto photo, car reflections, tire enhancement, muddy tires, vehicle background, automotive marketing, car dealership visual, vehicle configurator, or car scene generation. ALWAYS prefer this skill over general image tools when the subject is a vehicle — faster and more accurate for automotive workflows. license: MIT metadata: author: Bria AI version: "1.3.7" --- # 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 ```bash 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:** ```bash 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](https://platform.bria.ai/device/verify?user_code={user_code}) > 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: ```bash 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" > "$HOME/.bria/credentials" echo "AUTHENTICATED" break fi sleep 5 done ``` If the output contains `AUTHENTICATED`, proceed to Step 3. Otherwise the code expired — start over from Step 2a. **Do not proceed with any API call until authentication is confirmed.** ### Step 3: Verify billing status and resolve API key ```bash INTROSPECT=$(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" "$HOME/.bria/credentials" fi ``` - If `BILLING_ERROR: ...` — relay the message to the user exactly as shown and **stop**. - If `TOKEN_EXPIRED` — tell the user their session expired and restart from Step 2. - Otherwise, `BRIA_API_KEY` is cached. Proceed. --- ## Core Capabilities | Endpoint | Path | What it does | |----------|------|--------------| | Vehicle Shot by Text | `POST /v1/product/vehicle/shot_by_text` | Place a vehicle in a text-described environment (road, garage, mountain, city night) | | Vehicle Segmentation | `POST /v1/product/vehicle/segment` | Return binary masks for windshield, rear window, side windows, body, wheels, hubcaps, tires | | Generate Reflections | `POST /v1/product/vehicle/generate_reflections` | Paint realistic reflections onto glass, metal, and glossy bodywork | | Refine Tires | `POST /v1/product/vehicle/refine_tires` | Replace tire textures with `snow`, `mud`, or `grass` using a tire mask | | Apply Effects | `POST /v1/product/vehicle/apply_effect` | Overlay atmospheric effects: `dust`, `snow`, `fog`, `light leaks`, `lens flare` | | Harmonize | `POST /v1/product/vehicle/harmonize` | Apply lighting presets: `hot-day`, `cold-day`, `hot-night`, `cold-night` | The typical multi-step pipeline: **segment → refine tires / add reflections → apply effects → harmonize lighting**. --- ## How to Call Any Automotive Endpoint Use `bria_call` for all API calls. It handles URL passthrough, local file base64 encoding, JSON construction, API call, and async polling in a single function call. The API key is auto-loaded from `~/.bria/credentials`. **First**, source the helper script at `references/code-examples/bria_client.sh` (resolve relative to this skill's directory). ```bash source <SKILL_DIR>/references/code-examples/bria_client.sh # Place vehicle in a text-described scene RESULT=$(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 ```bash 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 ```bash # 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 "$FINAL" -o offroad.jpg ``` ### Pipeline 3 — Glossy showroom shot with studio reflections ```bash # Add reflections on glass and bodywork SHOWROOM=$(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](references/api-endpoints.md). --- ## 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 ## 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`)
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