Unlock Monocular Depth Estimation in Video with lucataco/depth-anything-video Actions

In the rapidly evolving field of computer vision, the ability to estimate depth from video content has tremendous applications, from augmented reality to autonomous driving systems. The lucataco/depth-anything-video spec provides developers with powerful Cognitive Actions that leverage advanced machine learning models to perform robust monocular depth estimation on full video files. These pre-built actions simplify the integration of depth estimation capabilities into your applications, allowing you to focus on building innovative solutions.

Prerequisites

Before diving into the Cognitive Actions, ensure you have the following:

• An API key for the Cognitive Actions platform.
• Basic familiarity with making HTTP requests and handling JSON data.
• A video file hosted online, accessible via a valid URI.

For authentication, you will typically pass your API key in the request headers.

Cognitive Actions Overview

Estimate Monocular Depth

The "Estimate Monocular Depth" action utilizes the Depth Anything model to estimate depth in video files. This action supports both relative and metric depth estimation, making it versatile for various high-level scene understanding tasks.

Input

The input for this action requires the following fields:

• video (required): A URI pointing to the input video file. The video must be accessible at this URL.
• modelType (optional): Specifies the model type to be used for processing the video. Options include:
  • vits (default)
  • vitb
  • vitl

Example Input:

{
  "video": "https://replicate.delivery/pbxt/KNKNfiWzJU5YxaSIsrJKBllp1TgjtvQ9urLNlN1biczFBPpe/dolphins.mp4",
  "modelType": "vits"
}

Output

Upon successful execution, this action returns a URL to the processed video file that contains the estimated depth data.

Example Output:

https://assets.cognitiveactions.com/invocations/d85eb338-2d58-4be2-ac77-9e602adbe638/1660de6b-d137-4faa-8b95-40434bf9be8c.mp4

Conceptual Usage Example (Python)

Here’s how you might call the "Estimate Monocular Depth" action using Python:

import requests
import json

# Replace with your Cognitive Actions API key and endpoint
COGNITIVE_ACTIONS_API_KEY = "YOUR_COGNITIVE_ACTIONS_API_KEY"
COGNITIVE_ACTIONS_EXECUTE_URL = "https://api.cognitiveactions.com/actions/execute" # Hypothetical endpoint

action_id = "e5096542-1b8c-44af-a19c-5a80be27a2c5" # Action ID for Estimate Monocular Depth

# Construct the input payload based on the action's requirements
payload = {
    "video": "https://replicate.delivery/pbxt/KNKNfiWzJU5YxaSIsrJKBllp1TgjtvQ9urLNlN1biczFBPpe/dolphins.mp4",
    "modelType": "vits"
}

headers = {
    "Authorization": f"Bearer {COGNITIVE_ACTIONS_API_KEY}",
    "Content-Type": "application/json"
}

try:
    response = requests.post(
        COGNITIVE_ACTIONS_EXECUTE_URL,
        headers=headers,
        json={"action_id": action_id, "inputs": payload} # Hypothetical structure
    )
    response.raise_for_status() # Raise an exception for bad status codes (4xx or 5xx)

    result = response.json()
    print("Action executed successfully:")
    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: {e.response.text}")

In this example, replace YOUR_COGNITIVE_ACTIONS_API_KEY with your actual API key. The payload is structured to match the input requirements of the "Estimate Monocular Depth" action, which includes the video URL and the model type.

Conclusion

Utilizing the lucataco/depth-anything-video Cognitive Actions allows developers to seamlessly integrate depth estimation capabilities into their applications, unlocking a host of possibilities across various domains. Whether you're processing video for augmented reality experiences or enhancing scene understanding in autonomous systems, these actions provide a powerful toolset to elevate your projects. Start exploring today, and consider the diverse applications of depth estimation in your next development endeavor!