inference-sdk

import os from inference_sdk import InferenceHTTPClient # Set your Roboflow API Key as an environment variable: # export ROBOFLOW_API_KEY="YOUR_API_KEY" api_key = os.environ.get('ROBOFLOW_API_KEY', '') if not api_key: print("Warning: ROBOFLOW_API_KEY environment variable not set. Inference might fail.") # Initialize the InferenceHTTPClient # Use "https://detect.roboflow.com" for hosted inference # Use "http://localhost:9001" if you're running a local inference server client = InferenceHTTPClient(api_url="https://detect.roboflow.com", api_key=api_key) # Specify your Roboflow model ID (e.g., "my-project/1") # Replace with a real public model or your own private model ID. model_id = "lego-brick-detector/1" # Example public model # Define the image source (can be a URL, local path, or base64 string) image_url = "https://media.roboflow.com/example_input.jpg" print(f"Attempting inference on {image_url} using model {model_id}...") try: # Perform inference result = client.infer(image_url, model_id=model_id) # Print results print("Inference successful!") print(f"Image dimensions: {result.image.width}x{result.image.height}") if result.predictions: print(f"Found {len(result.predictions)} predictions:") for pred in result.predictions: print(f" Class: {pred.class_name}, Confidence: {pred.confidence:.2f}, " f"Box: x={pred.x:.1f}, y={pred.y:.1f}, w={pred.width:.1f}, h={pred.height:.1f}") else: print("No predictions found.") except Exception as e: print(f"An error occurred during inference: {e}") print("Please ensure your ROBOFLOW_API_KEY is correct and the model ID is valid.")