/detect

import moondream as mdfrom PIL import Imageimport matplotlib.pyplot as pltimport matplotlib.patches as patches # Initialize with API keymodel = md.vl(api_key="your-api-key") # Load an imageimage = Image.open("path/to/image.jpg") # Detect objects (e.g., "person", "car", "face", etc.)result = model.detect(image, "person")detections = result["objects"]request_id = result["request_id"]print(f"Found {len(detections)} people")print(f"Request ID: {request_id}") # Visualize the detectionsplt.figure(figsize=(10, 10))plt.imshow(image)ax = plt.gca() for obj in detections:  # Convert normalized coordinates to pixel values  x_min = obj["x_min"] * image.width  y_min = obj["y_min"] * image.height  x_max = obj["x_max"] * image.width  y_max = obj["y_max"] * image.height   # Calculate width and height for the rectangle  width = x_max - x_min  height = y_max - y_min   # Create a rectangle patch  rect = patches.Rectangle(      (x_min, y_min), width, height,       linewidth=2, edgecolor='r', facecolor='none'  )  ax.add_patch(rect)  plt.text(      x_min, y_min, "Person",       color='white', fontsize=12,      bbox=dict(facecolor='red', alpha=0.5)  ) plt.axis('off')plt.savefig("output_with_detections.jpg")plt.show()