Video Frame Interpolation Serverless API
FILM synthesizes smooth, high-quality intermediate frames for fluid motion in videos with significant movement.
POST /v2/video-frame-interpolation · submit + poll 1# pip install "segmind>=1.1.0"
2# export SEGMIND_API_KEY="YOUR_API_KEY"
3from segmind import SegmindClient, InferenceFailed, InferenceTimeout
4
5# Async (v2) — recommended for long-running / video models.
6# run() blocks up to 600s; submit_async + job.wait(timeout=...) sets a longer
7# deadline and keeps the request_id so you can re-poll later.
8client = SegmindClient() # reads SEGMIND_API_KEY
9payload = {
10 "input_video": "https://segmind-resources.s3.amazonaws.com/output/568d37fa-1691-4ea5-aeb7-a904310a84df-2d5e91ed-66d2-4880-aa66-6aee09ad56f6.mp4",
11 "frame_multiplier": 2,
12 "output_fps": 30,
13 "preserve_audio": True,
14 "base64": False,
15}
16job = client.submit_async("video-frame-interpolation", **payload)
17print(job.request_id) # available immediately
18try:
19 result = job.wait(timeout=900, interval=2.0)
20 print(result["status"]) # COMPLETED
21 print(result.get("output")) # model output (e.g. video URL)
22except InferenceTimeout as e:
23 print("still running:", e.request_id) # re-poll later with this id
24except InferenceFailed as e:
25 print("failed:", e.detail)
26
27# Fast models (<=600s) can use the one-liner instead:
28# result = segmind.run("video-frame-interpolation", **payload) 1# pip install "segmind>=1.1.0"
2# export SEGMIND_API_KEY="YOUR_API_KEY"
3from segmind import SegmindClient, InferenceFailed, InferenceTimeout
4
5# Async (v2) — recommended for long-running / video models.
6# run() blocks up to 600s; submit_async + job.wait(timeout=...) sets a longer
7# deadline and keeps the request_id so you can re-poll later.
8client = SegmindClient() # reads SEGMIND_API_KEY
9payload = {
10 "input_video": "https://segmind-resources.s3.amazonaws.com/output/568d37fa-1691-4ea5-aeb7-a904310a84df-2d5e91ed-66d2-4880-aa66-6aee09ad56f6.mp4",
11 "frame_multiplier": 2,
12 "output_fps": 30,
13 "preserve_audio": True,
14 "base64": False,
15}
16job = client.submit_async("video-frame-interpolation", **payload)
17print(job.request_id) # available immediately
18try:
19 result = job.wait(timeout=900, interval=2.0)
20 print(result["status"]) # COMPLETED
21 print(result.get("output")) # model output (e.g. video URL)
22except InferenceTimeout as e:
23 print("still running:", e.request_id) # re-poll later with this id
24except InferenceFailed as e:
25 print("failed:", e.detail)
26
27# Fast models (<=600s) can use the one-liner instead:
28# result = segmind.run("video-frame-interpolation", **payload)API Endpoint
https://api.segmind.com/v1/video-frame-interpolationParameters
frame_multiplierrequiredintegerFrame multiplier for video processing
2Range: 1 - 10input_videorequiredstring (uri)Input video URL for processing
output_fpsrequiredintegerOutput frames per second for the processed video
30Range: 1 - 120base64optionalbooleanOutput as base64 encoded string
falsepreserve_audiooptionalbooleanWhether to preserve audio from the input video
trueResponse Type
Returns: Video
Asynchronous requests (v2)
Use Async for video, long-running (>~60s), or high-concurrency workloads; Sync is simplest for fast image & LLM calls. Async submits a request and you poll it to completion.
- 1
POST /v2/video-frame-interpolationSubmit — returns request_id, status_url, response_url
- 2
GET /v2/requests/{id}/statusPoll — until COMPLETED or FAILED
- 3
GET /v2/requests/{id}Result — final response body
Status states
- A FAILED request is served as HTTP 422 — the body still carries the error detail.
- An unknown or expired request_id returns HTTP 404.
- Results are retained for 1 hour, then expire.
- Content / RAI blocks surface as FAILED, not a separate state.
- Track completion by polling the status endpoint.
Common Error Codes
The API returns standard HTTP status codes. Detailed error messages are provided in the response body.
Bad Request
Invalid parameters or request format
Unauthorized
Missing or invalid API key
Forbidden
Insufficient permissions
Not Found
Model or endpoint not found
Insufficient Credits
Not enough credits to process request
Rate Limited
Too many requests
Server Error
Internal server error
Bad Gateway
Service temporarily unavailable
Timeout
Request timed out