import dataclasses as dc import io from functools import cache from typing import Any import gradio as gr import pillow_heif from environs import Env from finegrain import EditorAPIContext from gradio_image_annotation import image_annotator from gradio_imageslider import ImageSlider from PIL import Image pillow_heif.register_heif_opener() pillow_heif.register_avif_opener() env = Env() env.read_env() with env.prefixed("ERASER_"): API_USER: str | None = env.str("API_USER") API_PASSWORD: str | None = env.str("API_PASSWORD") API_URL: str | None = env.str("API_URL", None) CA_BUNDLE: str | None = env.str("CA_BUNDLE", None) @cache def _ctx() -> EditorAPIContext: assert API_USER is not None assert API_PASSWORD is not None ctx = EditorAPIContext(user=API_USER, password=API_PASSWORD, priority="low") if CA_BUNDLE: ctx.verify = CA_BUNDLE if API_URL: ctx.base_url = API_URL return ctx def resize(image: Image.Image, shortest_side: int = 768) -> Image.Image: if image.width <= shortest_side and image.height <= shortest_side: return image if image.width < image.height: return image.resize(size=(shortest_side, int(shortest_side * image.height / image.width))) return image.resize(size=(int(shortest_side * image.width / image.height), shortest_side)) @dc.dataclass(kw_only=True) class ProcessParams: image: Image.Image prompt: str | None = None bbox: tuple[int, int, int, int] | None = None async def _process(ctx: EditorAPIContext, params: ProcessParams) -> Image.Image: with io.BytesIO() as f: params.image.save(f, format="JPEG") response = await ctx.request("POST", "state/upload", files={"file": f}) st_input = response.json()["state"] if params.bbox: segment_input_st = st_input segment_params = {"bbox": list(params.bbox)} else: assert params.prompt segment_input_st = await ctx.ensure_skill( f"infer-bbox/{st_input}", {"product_name": params.prompt}, ) segment_params = {} st_mask = await ctx.ensure_skill(f"segment/{segment_input_st}", segment_params) st_erased = await ctx.ensure_skill(f"erase/{st_input}/{st_mask}", {"mode": "free"}) response = await ctx.request( "GET", f"state/image/{st_erased}", params={"format": "JPEG", "resolution": "DISPLAY"}, ) f = io.BytesIO() f.write(response.content) f.seek(0) return Image.open(f) def process_bbox(prompts: dict[str, Any]) -> tuple[Image.Image, 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) resized_img = resize(img) bbox = [box[k] for k in ["xmin", "ymin", "xmax", "ymax"]] if resized_img.width != img.width: bbox = [int(v * resized_img.width / img.width) for v in bbox] output_image = _ctx().run_one_sync( _process, ProcessParams( image=resized_img, bbox=(bbox[0], bbox[1], bbox[2], bbox[3]), ), ) return (img, output_image) def on_change_bbox(prompts: dict[str, Any] | None): return gr.update(interactive=prompts is not None and len(prompts["boxes"]) > 0) def process_prompt(img: Image.Image, prompt: str) -> tuple[Image.Image, Image.Image]: resized_img = resize(img) output_image = _ctx().run_one_sync( _process, ProcessParams(image=resized_img, prompt=prompt), ) return (img, output_image) def on_change_prompt(img: Image.Image | None, prompt: str | None): return gr.update(interactive=bool(img and prompt)) TITLE = """
🥳 We're launching our API! It's way faster and more accurate than this space, so check it out! Try it now for free using our Editor app! 🚀

Finegrain Object Eraser

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.

[Discord] [GitHub]

""" with gr.Blocks() as demo: gr.HTML(TITLE) 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 = ImageSlider(label="Output") with gr.Row(): btn = gr.ClearButton(components=[oimg], value="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], api_name=False, ) 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", ], ] ex = gr.Examples( examples=examples, 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 = ImageSlider(label="Output") with gr.Row(): btn = gr.ClearButton(components=[oimg], value="Erase Object", interactive=False) annotator.change( fn=on_change_bbox, inputs=[annotator], outputs=[btn], ) btn.click( fn=process_bbox, inputs=[annotator], outputs=[oimg], api_name=False, ) 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}], }, ] ex = gr.Examples( examples=examples, inputs=[annotator], outputs=[oimg], fn=process_bbox, cache_examples=True, ) demo.queue(max_size=30, api_open=False) demo.launch(show_api=False)