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import gradio as gr
import numpy as np
import random
with gr.Blocks() as demo:
section_labels = [
"apple",
"banana",
"carrot",
"donut",
"eggplant",
"fish",
"grapes",
"hamburger",
"ice cream",
"juice",
]
with gr.Row():
num_boxes = gr.Slider(0, 5, 2, step=1, label="Number of boxes")
num_segments = gr.Slider(0, 5, 1, step=1, label="Number of segments")
with gr.Row():
img_input = gr.Image()
img_output = gr.AnnotatedImage(
color_map={"banana": "#a89a00", "carrot": "#ffae00"}
)
section_btn = gr.Button("Identify Sections")
selected_section = gr.Textbox(label="Selected Section")
def section(img, num_boxes, num_segments):
sections = []
for a in range(num_boxes):
x = random.randint(0, img.shape[1])
y = random.randint(0, img.shape[0])
w = random.randint(0, img.shape[1] - x)
h = random.randint(0, img.shape[0] - y)
sections.append(((x, y, x + w, y + h), section_labels[a]))
for b in range(num_segments):
x = random.randint(0, img.shape[1])
y = random.randint(0, img.shape[0])
r = random.randint(0, min(x, y, img.shape[1] - x, img.shape[0] - y))
mask = np.zeros(img.shape[:2])
for i in range(img.shape[0]):
for j in range(img.shape[1]):
dist_square = (i - y) ** 2 + (j - x) ** 2
if dist_square < r**2:
mask[i, j] = round((r**2 - dist_square) / r**2 * 4) / 4
sections.append((mask, section_labels[b + num_boxes]))
return (img, sections)
section_btn.click(section, [img_input, num_boxes, num_segments], img_output)
def select_section(evt: gr.SelectData):
return section_labels[evt.index]
img_output.select(select_section, None, selected_section)
if __name__ == "__main__":
demo.launch()
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