app.py

import io
from typing import Any

import gradio as gr
import httpx
from environs import Env
from gradio_image_annotation import image_annotator
from PIL import Image

env = Env()
env.read_env()

with env.prefixed("ERASER_"):
    API_URL: str = str(env.str("API_URL", "https://spaces.finegrain.ai/eraser"))
    API_KEY: str | None = env.str("API_KEY", None)
    CA_BUNDLE: str | None = env.str("CA_BUNDLE", None)

auth = None if API_KEY is None else httpx.BasicAuth("hf", API_KEY)


def process_bbox(prompts: dict[str, Any]) -> Image.Image:
    assert isinstance(img := prompts["image"], Image.Image)
    assert isinstance(boxes := prompts["boxes"], list)
    assert len(boxes) == 1
    assert isinstance(box := boxes[0], dict)
    data = {"bbox": ",".join([str(box[k]) for k in ["xmin", "ymin", "xmax", "ymax"]])}
    with io.BytesIO() as f:
        img.save(f, format="JPEG")
        r = httpx.post(
            API_URL,
            data=data,
            files={"file": f},
            verify=CA_BUNDLE or True,
            timeout=30.0,
            auth=auth,
        )
    r.raise_for_status()
    return Image.open(io.BytesIO(r.content))


def on_change_bbox(prompts: dict[str, Any]):
    return gr.update(interactive=len(prompts["boxes"]) > 0)


def process_prompt(img: Image.Image, prompt: str) -> Image.Image:
    data = {"prompt": prompt}
    with io.BytesIO() as f:
        img.save(f, format="JPEG")
        r = httpx.post(
            API_URL,
            data=data,
            files={"file": f},
            verify=CA_BUNDLE or True,
            timeout=30.0,
            auth=auth,
        )
    r.raise_for_status()
    return Image.open(io.BytesIO(r.content))


def on_change_prompt(img: Image.Image | None, prompt: str | None):
    return gr.update(interactive=bool(img and prompt))


desc = """
<center>
<h1>Object Eraser Powered by Refiners</h1>

<p style="font-size: 1.25rem;">
<a href="https://refine.rs" target="_blank">[refiners]</a>
<a href="https://finegrain.ai/" target="_blank">[finegrain]</a>
</p>

<p>
Erase any object from your image just by naming it — no manual work required!
Not only will the object disappear, but so will its effects on the scene, like shadows or reflections.
</p>

<p>
If you enjoyed this space, please consider starring Refiners on GitHub!
&nbsp;
<a href="https://github.com/finegrain-ai/refiners" target="_blank">
  <img
    src="https://img.shields.io/github/stars/finegrain-ai/refiners?style=social"
    style="display: inline; vertical-align: middle;"
  />
</a>
</p>


</center>
"""

with gr.Blocks() as demo:
    gr.HTML(desc)
    with gr.Tab("By prompt", id="tab_prompt"):
        with gr.Row():
            with gr.Column():
                iimg = gr.Image(type="pil", label="Input")
                prompt = gr.Textbox(label="What should we erase?")
            with gr.Column():
                oimg = gr.Image(show_label=False, label="Output")
        with gr.Row():
            btn = gr.Button("Erase Object", interactive=False)
        for inp in [iimg, prompt]:
            inp.change(
                fn=on_change_prompt,
                inputs=[iimg, prompt],
                outputs=[btn],
            )
        btn.click(fn=process_prompt, inputs=[iimg, prompt], outputs=[oimg])

        ex = gr.Examples(
            examples=[
                [
                    "examples/white-towels-rattan-basket-white-table-with-bright-room-background.jpg",
                    "soap",
                ],
                [
                    "examples/interior-decor-with-mirror-potted-plant.jpg",
                    "potted plant",
                ],
                [
                    "examples/detail-ball-basketball-court-sunset.jpg",
                    "basketball",
                ],
                [
                    "examples/still-life-device-table_23-2150994394.jpg",
                    "glass of water",
                ],
                [
                    "examples/knife-fork-green-checkered-napkin_140725-63576.jpg",
                    "knife and fork",
                ],
                [
                    "examples/city-night-with-architecture-vibrant-lights_23-2149836930.jpg",
                    "frontmost black car on right lane",
                ],
                [
                    "examples/close-up-coffee-latte-wooden-table_23-2147893063.jpg",
                    "coffee cup on plate",
                ],
                [
                    "examples/empty-chair-with-vase-plant_74190-2078.jpg",
                    "chair",
                ],
            ],
            inputs=[iimg, prompt],
            outputs=[oimg],
            fn=process_prompt,
            cache_examples=True,
        )
    with gr.Tab("By bounding box", id="tab_bb"):
        with gr.Row():
            with gr.Column():
                annotator = image_annotator(
                    image_type="pil",
                    disable_edit_boxes=True,
                    show_download_button=False,
                    show_share_button=False,
                    single_box=True,
                    label="Input",
                )
            with gr.Column():
                oimg = gr.Image(show_label=False, label="Output")
        with gr.Row():
            btn = gr.Button("Erase Object", interactive=False)
        annotator.change(
            fn=on_change_bbox,
            inputs=[annotator],
            outputs=[btn],
        )
        btn.click(fn=process_bbox, inputs=[annotator], outputs=[oimg])

        ex = gr.Examples(
            examples=[
                {
                    "image": "examples/white-towels-rattan-basket-white-table-with-bright-room-background.jpg",
                    "boxes": [{"xmin": 836, "ymin": 475, "xmax": 1125, "ymax": 1013}],
                },
                {
                    "image": "examples/interior-decor-with-mirror-potted-plant.jpg",
                    "boxes": [{"xmin": 47, "ymin": 907, "xmax": 397, "ymax": 1633}],
                },
                {
                    "image": "examples/detail-ball-basketball-court-sunset.jpg",
                    "boxes": [{"xmin": 673, "ymin": 954, "xmax": 911, "ymax": 1186}],
                },
                {
                    "image": "examples/still-life-device-table_23-2150994394.jpg",
                    "boxes": [{"xmin": 429, "ymin": 586, "xmax": 571, "ymax": 834}],
                },
                {
                    "image": "examples/knife-fork-green-checkered-napkin_140725-63576.jpg",
                    "boxes": [{"xmin": 972, "ymin": 226, "xmax": 1092, "ymax": 1023}],
                },
                {
                    "image": "examples/city-night-with-architecture-vibrant-lights_23-2149836930.jpg",
                    "boxes": [{"xmin": 215, "ymin": 637, "xmax": 411, "ymax": 855}],
                },
                {
                    "image": "examples/close-up-coffee-latte-wooden-table_23-2147893063.jpg",
                    "boxes": [{"xmin": 255, "ymin": 456, "xmax": 1080, "ymax": 1064}],
                },
                {
                    "image": "examples/empty-chair-with-vase-plant_74190-2078.jpg",
                    "boxes": [{"xmin": 35, "ymin": 320, "xmax": 383, "ymax": 983}],
                },
            ],
            inputs=[annotator],
            outputs=[oimg],
            fn=process_bbox,
            cache_examples=True,
        )

demo.launch(show_api=False)