Advanced Event Understanding
Introduction
Welcome to the Advanced Event Understanding API, a cutting-edge solution for sophisticated event analysis and interpretation. Our API harnesses the power of advanced AI technology to provide deep, real-time insights for your security and surveillance applications. By processing multiple images and associated metadata, our system offers unparalleled event comprehension, enabling you to make informed decisions quickly and efficiently.
Key Features
Efficient Multi-Image Processing: Analyze 5 or more strategic images per event, providing comprehensive understanding without the need for extensive data transfer.
Advanced AI Interpretation: Extract deep insights from limited visual data, offering sophisticated event analysis that rivals full video processing.
Real-time Analysis: Receive instant results for time-critical decision-making.
Flexible Integration: Seamlessly incorporate our RESTful API into your existing systems.
Secure Communication: Protect your data with robust API key authentication.
Authentication
All API requests require authentication using an API key. Include your API key in the x-api-key header for all requests. If you don't have an API key, you can obtain one by contacting our support team at [email protected].
API Endpoints
Returns the overall health status of the application
import requests
url = "https://k0.traces.cloud/health"
headers = {"x-api-key": "TRACES_API_KEY"}
response = requests.get(url, headers=headers)
print(response.json())
{
"status": "healthy"
}Handle multipart form data containing metadata and images, process them, and return a response with filtering report and task ID for advanced understanding.
Traces API key
JSON string containing event metadata
import requests
import json
import os
def process_event(image_paths, metadata):
url = 'https://k0.traces.cloud/api/v1/event/process'
headers = {'x-api-key': 'TRACES_API_KEY'}
files = {}
for i, path in enumerate(image_paths):
with open(path, 'rb') as img_file:
files[f'image_{i}'] = (f'image_{i}.png', img_file.read())
data = {'metadata': json.dumps(metadata)}
response = requests.post(url, headers=headers, data=data, files=files)
return response.json()
# Example usage
image_paths = [
'path/to/image1.png',
'path/to/image2.png',
'path/to/image3.png',
'path/to/image4.png',
'path/to/image5.png'
]
metadata = {
'camera_id': 'b5271b30-aecd-4897-bc95-ff25c8466b9t',
'event_id': 'ddf27b34-d3b5-41a5-b2a6-3873a589ec09',
'timestamp': 1585840725
}
result = process_event(image_paths, metadata)
print(json.dumps(result, indent=2))
{
"advanced_understanding_task_id": "123e4567-e89b-12d3-a456-426614174000",
"filtering_report": {
"alarm_confirmed": true,
"alarm_confidence": 0.95,
"triggered_by": [
{
"object_type": "vehicle",
"object_class": "truck",
"action": "moving",
"bbox": [
10,
20,
100,
200
],
"frame_id": 0,
"direction": "None",
"object_color": "red"
}
]
}
}Retrieve the advanced understanding results for a previously processed event.
The task ID returned from the process event endpoint
Traces API key
import requests
url = "https://k0.traces.cloud/api/v1/event/advanced_understanding"
params = {"task_id": "123e4567-e89b-12d3-a456-426614174000"}
headers = {"x-api-key": "TRACES_API_KEY"}
response = requests.get(url, params=params, headers=headers)
{
"status": "completed",
"result": {
"event_summary": "A person wearing a light-colored hoodie approaches a black car parked on the side of a street. The person appears to attempt to open the side door, but the car is locked. The person gains entry to the car.",
"predicted_attributes": {
"people_descriptions": [
"light-colored hoodie",
"dark jeans"
],
"people_actions": [
"trying to break in"
],
"logos": [
"None"
],
"vehicle_descriptions": [
"a black car"
],
"vehicle_actions": [
"parked"
],
"suspicion_status": "highly suspicious"
}
}
}Examples
{
"status": "completed",
"result": {
"event_summary": "A person wearing a light-colored hoodie approaches a black car parked on the side of a street. The person appears to attempt to open the side door, but the car is locked. The person gains entry to the car.",
"predicted_attributes": {
"people_descriptions": [
"light-colored hoodie",
"dark jeans"
],
"people_actions": [
"trying to break in"
],
"logos": [
"None"
],
"vehicle_descriptions": [
"a black car"
],
"vehicle_actions": [
"parked"
],
"suspicion_status": "highly suspicious"
}
}
}Advanced Features
Our Advanced Event Understanding API offers a range of sophisticated capabilities:
Multi-image Analysis: Process 5 or more images per event for comprehensive understanding.
Object Detection and Classification: Identify and categorize objects, people, and vehicles in the scene.
Action Recognition: Understand and interpret the actions and behaviors of detected entities.
Contextual Analysis: Evaluate the overall situation and relationships between objects and actions.
Natural Language Summaries: Generate human-readable descriptions of events for quick comprehension.
Suspicion Assessment: Automatically evaluate the potential threat level of events.
Last updated
Was this helpful?