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import gradio as gr
from PIL import Image, ImageDraw
from transparent_background import Remover
import numpy as np
from gradio_imageslider import ImageSlider
def resize(img: Image, target_size_px: int):
aspect_ratio = img.width / img.height
if img.width > img.height:
new_width = target_size_px
new_height = int(target_size_px / aspect_ratio)
else:
new_height = target_size_px
new_width = int(target_size_px * aspect_ratio)
img = img.resize((new_width, new_height))
return img
def infer(img: Image):
img_resized = resize(img, 512)
remover = Remover(mode="fast")
masked_image = remover.process(img_resized, type="map")
gray_image = masked_image.convert("L")
binary_image = gray_image.point(lambda x: 0 if x < 128 else 255, "1")
image_array = np.array(binary_image)
white_pixels = np.where(image_array == True)
x_coords = white_pixels[1]
y_coords = white_pixels[0]
min_x = np.min(x_coords)
max_x = np.max(x_coords)
min_y = np.min(y_coords)
max_y = np.max(y_coords)
draw = ImageDraw.Draw(img_resized)
draw.rectangle([(min_x, min_y), (max_x, max_y)], outline="red", width=2)
return img_resized, masked_image
gr.Interface(
fn=infer,
description="""
This space performs salient object detection on an image uploaded by the user. I.e. it will detect the object(s) in the image foreground and draw a red rectangle around it.
It uses the [transparent-background](https://github.com/plemeri/transparent-background) library, which is built on [InSPyReNet](https://github.com/plemeri/inspyrenet).
""",
inputs=gr.components.Image(type="pil", label="Input Image"),
outputs=ImageSlider(label="Output", type="pil"),
title="Salient Object Detection",
).launch()
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