AnnotatedImage

import gradio as gr

def detect_objects(image):
    # Returns (image, [(mask, label), ...])  
    annotations = [
        ((10, 20, 100, 150), "cat"),  # Bounding box
        ((200, 50, 300, 200), "dog")   # Bounding box
    ]
    return (image, annotations)

gr.Interface(
    fn=detect_objects,
    inputs=gr.Image(),
    outputs=gr.AnnotatedImage()
).launch()

import gradio as gr
import numpy as np

def detect(image):
    # Simulated detections
    boxes = [
        ((50, 50, 200, 200), "person"),
        ((250, 100, 400, 300), "car")
    ]
    return (image, boxes)

gr.Interface(
    fn=detect,
    inputs=gr.Image(),
    outputs=gr.AnnotatedImage(color_map={
        "person": "#00FF00",
        "car": "#FF0000"
    })
).launch()

import gradio as gr
import numpy as np

def segment(image):
    # Create a segmentation mask
    h, w = image.shape[:2]
    mask = np.zeros((h, w))
    mask[50:150, 50:150] = 0.8  # Confidence mask
    
    annotations = [(mask, "object")]
    return (image, annotations)

gr.Interface(
    fn=segment,
    inputs=gr.Image(),
    outputs=gr.AnnotatedImage()
).launch()