inference-gpu

import os from inference import get_roboflow_model # Set your Roboflow API key, project ID, and version ROBOFLOW_API_KEY = os.environ.get('ROBOFLOW_API_KEY', 'YOUR_API_KEY') ROBOFLOW_MODEL_ID = os.environ.get('ROBOFLOW_MODEL_ID', 'YOUR_PROJECT/YOUR_VERSION') # Ensure API key is set if ROBOFLOW_API_KEY == 'YOUR_API_KEY': print("Warning: ROBOFLOW_API_KEY not set. Using placeholder.") # Load the model print(f"Loading model: {ROBOFLOW_MODEL_ID}") model = get_roboflow_model(model_id=ROBOFLOW_MODEL_ID, api_key=ROBOFLOW_API_KEY) # Example inference (using a dummy image path) # Replace 'your_image.jpg' with a real image path or PIL Image object # For local testing, you might need a dummy image or to adjust the source. try: # This part assumes you have an image file named 'test_image.jpg' # For a real example, replace with a valid image path. # Download a sample image for testing, e.g., from Roboflow Universe. # Example: 'https://i.imgur.com/your_image.jpg' results = model.infer(image_path="test_image.jpg") print("Inference successful!") # print(results) except FileNotFoundError: print("Error: test_image.jpg not found. Please provide a valid image path for inference.") except Exception as e: print(f"An error occurred during inference: {e}") # You can also infer on a PIL Image or numpy array # from PIL import Image # import numpy as np # dummy_image = Image.new('RGB', (640, 480), color = 'red') # results = model.infer(image=np.array(dummy_image)) # print("Inference successful with dummy image!")