Effortlessly Clip and Render Videos with GPU Acceleration

11 May 2025

The GPU Accelerated Video Clipper API is a powerful tool designed for developers looking to streamline the process of video rendering and clipping from openpilot route data. This API leverages the immense processing power of Nvidia GPUs, enabling faster and more efficient video processing than traditional methods. By integrating this API into your applications, you can significantly reduce the time required to create high-quality video clips, making it an ideal solution for various use cases in automotive data analysis, media production, and more.

Imagine you’re developing a dashboard for visualizing autonomous vehicle data. The ability to quickly clip and render videos from route data allows you to create engaging visual content that enhances user experience. Whether it's for educational purposes, testing, or simply sharing unique driving experiences, the GPU Accelerated Video Clipper API simplifies this task.

jwt: Optional JWT Token for restricted routes.
notes: Personal reference notes that do not influence output.
metric: Boolean to render video in metric units (km/h).
routeUrl: URL or Route ID from comma connect.
clipSizeMb: Approximate size of the output clip in MB (5 to 200 MB).
videoFormat: Choose between 'auto', 'H.264', or 'HEVC'.
startTimeSec: Start time in seconds for Route ID input.
speedModifier: Ratio for rendering speed (0.1 to 7).
clipDurationSec: Length of the clip in seconds (5 to 300 seconds).
videoRenderType: Various rendering modes like UI, Forward, Wide, etc.
overlayPositionH: Horizontal position of the forward overlay.
preRenderDuration: Time to start the video before recording for UI renders.

Example Input:

{
  "jwt": "",
  "notes": "",
  "metric": false,
  "routeUrl": "https://connect.comma.ai/a2a0ccea32023010/1690488131496/1690488151496",
  "clipSizeMb": 9,
  "videoFormat": "auto",
  "startTimeSec": 50,
  "speedModifier": 1,
  "clipDurationSec": 20,
  "videoRenderType": "ui",
  "overlayPositionH": 2.2,
  "preRenderDuration": 5
}

Expected Output

The output is a URL that links to the rendered video clip, ready for viewing or further processing.

Example Output:

https://assets.cognitiveactions.com/invocations/3bcc7ff4-1fac-4747-be80-feb63a18f056/b4eb807e-65f0-44d0-9db6-a3badcee6160.mp4

Use Cases for this Action

Automotive Testing: Quickly create video clips of driving tests for analysis and improvement.
User Engagement: Provide users with personalized video content from their driving data, enhancing the overall experience.
Educational Content: Use the clips for tutorials or demonstrations in driver education, showcasing how autonomous systems operate in real-time scenarios.


```python
import requests
import json

# Replace with your actual Cognitive Actions API key and endpoint
# Ensure your environment securely handles the API key
COGNITIVE_ACTIONS_API_KEY = "YOUR_COGNITIVE_ACTIONS_API_KEY"
# This endpoint URL is hypothetical and should be documented for users
COGNITIVE_ACTIONS_EXECUTE_URL = "https://api.cognitiveactions.com/actions/execute"

action_id = "d7a6b306-6b6f-4150-b15e-5b79a3b4085f" # Action ID for: Render and Clip Video from Openpilot Route Data

# Construct the exact input payload based on the action's requirements
# This example uses the predefined example_input for this action:
payload = {
  "jwt": "",
  "notes": "",
  "metric": false,
  "routeUrl": "https://connect.comma.ai/a2a0ccea32023010/1690488131496/1690488151496",
  "clipSizeMb": 9,
  "videoFormat": "auto",
  "startTimeSec": 50,
  "speedModifier": 1,
  "clipDurationSec": 20,
  "videoRenderType": "ui",
  "overlayPositionH": 2.2,
  "preRenderDuration": 5
}

headers = {
    "Authorization": f"Bearer {COGNITIVE_ACTIONS_API_KEY}",
    "Content-Type": "application/json",
    # Add any other required headers for the Cognitive Actions API
}

# Prepare the request body for the hypothetical execution endpoint
request_body = {
    "action_id": action_id,
    "inputs": payload
}

print(f"--- Calling Cognitive Action: {action.name or action_id} ---")
print(f"Endpoint: {COGNITIVE_ACTIONS_EXECUTE_URL}")
print(f"Action ID: {action_id}")
print("Payload being sent:")
print(json.dumps(request_body, indent=2))
print("------------------------------------------------")

try:
    response = requests.post(
        COGNITIVE_ACTIONS_EXECUTE_URL,
        headers=headers,
        json=request_body
    )
    response.raise_for_status() # Raise an exception for bad status codes (4xx or 5xx)

    result = response.json()
    print("Action executed successfully. Result:")
    print(json.dumps(result, indent=2))

except requests.exceptions.RequestException as e:
    print(f"Error executing action {action_id}: {e}")
    if e.response is not None:
        print(f"Response status: {e.response.status_code}")
        try:
            print(f"Response body: {e.response.json()}")
        except json.JSONDecodeError:
            print(f"Response body (non-JSON): {e.response.text}")
    print("------------------------------------------------")


## Conclusion
The GPU Accelerated Video Clipper API offers a robust solution for developers aiming to enhance their video processing capabilities. By simplifying the clipping and rendering of video from openpilot route data, it opens up numerous possibilities for automotive applications, user engagement, and educational content. Start integrating this API into your projects today and unlock the potential of GPU-accelerated video processing!

Effortlessly Clip and Render Videos with GPU Acceleration

Prerequisites

Render and Clip Video from Openpilot Route Data

Input Requirements

Expected Output

Use Cases for this Action