API Reference
API Playground
How to test endpoints quickly with real API keys and production-like payloads.
API Reference
How to test endpoints quickly with real API keys and production-like payloads.
Use this page as a test harness before integrating SDK or backend workers.
For visual JSON testing, use Composition Builder: https://removebgvideo.com/composition-builder/
| Step | Action | Expected Result |
|---|---|---|
| 1 | Create job via POST /v1/jobs | Receive job_id |
| 2 | Start job via POST /v1/jobs/{job_id}/start | status moves to processing |
| 3 | Poll GET /v1/jobs/{job_id} | status becomes completed or failed |
| 4 | Open output_url | Processed video is downloadable/playable |
# 1) Create job
curl -X POST https://api.removebgvideo.com/v1/jobs \
-H "X-Api-Key: YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"video_url": "https://cdn.removebgvideo.com/uploads/your-video.mp4",
"model": "original",
"output_format": "webm",
"background": { "type": "transparent" },
"auto_start": false
}'
# 2) Start job (replace JOB_ID)
curl -X POST https://api.removebgvideo.com/v1/jobs/JOB_ID/start \
-H "X-Api-Key: YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "pro",
"text_prompt": "person, clothing accessories, glowing ring",
"background": { "type": "transparent" }
}'
# 3) Poll status
curl -X GET https://api.removebgvideo.com/v1/jobs/JOB_ID \
-H "X-Api-Key: YOUR_API_KEY"| Check | How to Verify |
|---|---|
| Authentication | Call endpoint with valid and invalid key, confirm 200 vs 401 |
| Rate limits | Burst test and confirm 429 handling with backoff |
| Idempotency | Retry same request and verify no duplicate side effects |
| Observability | Confirm request_id/job_id appears in logs and dashboards |
| Scenario | Payload Focus | Expected Outcome |
|---|---|---|
| Baseline quality | model=original + transparent | Stable edges and usable alpha |
| Speed profile | model=light | Lower latency, acceptable quality on simple scenes |
| Prompt targeting | model=pro + text_prompt | Correct subject isolation by prompt intent |
| Portrait optimization | model=human | Strong people segmentation performance |