Update

.pre-commit-config.yaml

@@ -14,7 +14,7 @@ repos:
       - id: requirements-txt-fixer
       - id: trailing-whitespace
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.11.10
+    rev: v0.15.4
     hooks:
       - id: ruff
         args: ["--fix"]

.python-version

@@ -1 +1 @@
-3.10
+3.12

README.md

@@ -4,7 +4,8 @@ emoji: 📉
 colorFrom: indigo
 colorTo: blue
 sdk: gradio
-sdk_version: 5.39.0
+sdk_version: 6.8.0
+python_version: 3.12.12
 app_file: app.py
 pinned: false
 license: mit

app.py

@@ -1,6 +1,12 @@
-#!/usr/bin/env python
+"""ViTMatte demo using TrimapEditor for trimap input."""
 
+from __future__ import annotations
+
+import base64
+import json
 import os
+from io import BytesIO
+from pathlib import Path
 
 import gradio as gr
 import numpy as np
@@ -8,41 +14,22 @@ import PIL.Image
 import spaces
 import torch
 from transformers import VitMatteForImageMatting, VitMatteImageProcessor
+from trimap_editor import TrimapEditor
 
 DESCRIPTION = """\
 # [ViTMatte](https://github.com/hustvl/ViTMatte)
 
-This is a demo of [ViTMatte](https://github.com/hustvl/ViTMatte), an image matting method that uses Vision Transformers (ViT) to accurately extract the foreground from an image.
-It predicts a soft alpha matte to help separate the subject from the background — even tricky areas like hair and fur!
-
-You've got two ways to get started:
-
-### 🖼️ Option 1: Upload Image & Trimap
-- Upload your original image.
-- Upload a **trimap**: a helper image that labels regions as **foreground (white)**, **background (black)**, and **unknown (gray)**.
-- The trimap must be a **grayscale image** containing only three pixel values:
-  - `0` for **background**
-  - `128` for **unknown**
-  - `255` for **foreground**
-- The model will use this trimap to generate the alpha matte and extract the foreground.
-
-### ✏️ Option 2: Draw Your Own Trimap
-- Upload just your image.
-- Go to the **"Draw Trimap"** tab to start drawing masks.
-- Use the tools to mark:
-  - **Foreground** (e.g. the subject),
-  - **Unknown** (areas where the boundary is unclear).
-- Once you're done, click the **"Generate Trimap"** button to generate the trimap from your drawing.
-
-### ✨ Optional: Replace Background
-Want to swap the background? Just check the **"Replace Background"** option and choose a new background image.
-The app will blend your extracted subject with the new background seamlessly!
-
+Image matting with Vision Transformers — accurately extract the foreground
+from an image, even tricky areas like hair and fur!
 
+1. **Upload** an image (or click an example below).
+2. **Draw** foreground (green) and unknown (blue) regions. Press **?** for shortcuts.
+3. Click **Run** to generate the alpha matte.
 """
 
-device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
+_ASSETS_DIR = Path(__file__).parent / "assets"
 
+device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
 MAX_IMAGE_SIZE = int(os.getenv("MAX_IMAGE_SIZE", "1500"))
 MODEL_ID = os.getenv("MODEL_ID", "hustvl/vitmatte-small-distinctions-646")
 
@@ -50,93 +37,90 @@ processor = VitMatteImageProcessor.from_pretrained(MODEL_ID)
 model = VitMatteForImageMatting.from_pretrained(MODEL_ID).to(device)
 
 
-def resize_input_image(image: PIL.Image.Image | None) -> PIL.Image.Image:
-    if image is None:
-        return None
-    if max(image.size) > MAX_IMAGE_SIZE:
-        w, h = image.size
-        scale = MAX_IMAGE_SIZE / max(w, h)
-        new_w = int(w * scale)
-        new_h = int(h * scale)
-        gr.Info(
-            f"The uploaded image exceeded the maximum resolution limit of {MAX_IMAGE_SIZE}px. It has been resized to {new_w}x{new_h}."
-        )
-        return image.resize((new_w, new_h))
-    return image
-
-
-def binarize_mask(mask: np.ndarray) -> np.ndarray:
-    mask[mask > 0] = 1
-    return mask
-
-
-def update_trimap(mask_editor: dict) -> np.ndarray:
-    foreground = mask_editor["layers"][0]
-    foreground = binarize_mask(foreground)
-
-    unknown = mask_editor["layers"][1]
-    unknown = binarize_mask(unknown)
-
-    trimap = np.zeros_like(foreground)
-    trimap[unknown > 0] = 128
-    trimap[foreground > 0] = 255
-    return trimap
-
-
-def adjust_background_image(background_image: PIL.Image.Image, target_size: tuple[int, int]) -> PIL.Image.Image:
-    target_w, target_h = target_size
-    bg_w, bg_h = background_image.size
-
-    scale = max(target_w / bg_w, target_h / bg_h)
-    new_bg_w = int(bg_w * scale)
-    new_bg_h = int(bg_h * scale)
-    background_image = background_image.resize((new_bg_w, new_bg_h))
-    left = (new_bg_w - target_w) // 2
-    top = (new_bg_h - target_h) // 2
-    right = left + target_w
-    bottom = top + target_h
-    return background_image.crop((left, top, right, bottom))
-
-
-def replace_background(
-    image: PIL.Image.Image, alpha: np.ndarray, background_image: PIL.Image.Image | None
+def _resize_on_upload(value: str | None) -> PIL.Image.Image:
+    """Downscale the image on upload if it exceeds MAX_IMAGE_SIZE.
+
+    Only fires for fresh uploads (no trimapBase64 yet).
+    Returns gr.skip() when no resize is needed so the editor is untouched.
+    """
+    if not value:
+        return gr.skip()
+    d = json.loads(value)
+    if "trimapBase64" in d:
+        return gr.skip()
+    w, h = d.get("width", 0), d.get("height", 0)
+    if max(w, h) <= MAX_IMAGE_SIZE:
+        return gr.skip()
+    image_url = d.get("image", "")
+    if not image_url:
+        return gr.skip()
+    # .change() receives raw postprocess() values which still have the
+    # Gradio file-serving prefix (JS strips it only in commitValue()).
+    image_path = image_url.removeprefix("/gradio_api/file=")
+    image = PIL.Image.open(image_path).convert("RGB")
+    scale = MAX_IMAGE_SIZE / max(w, h)
+    new_w, new_h = int(w * scale), int(h * scale)
+    gr.Info(f"Image resized from {w}x{h} to {new_w}x{new_h} (max {MAX_IMAGE_SIZE}px).")
+    return image.resize((new_w, new_h))
+
+
+def _parse_editor(value: str | None) -> tuple[PIL.Image.Image, PIL.Image.Image]:
+    """Extract image and trimap from TrimapEditor JSON value."""
+    if not value:
+        raise gr.Error("Upload an image and draw a trimap first.")
+    d = json.loads(value)
+
+    # Image
+    image_url = d.get("image", "")
+    if not image_url:
+        raise gr.Error("No image loaded.")
+    image = PIL.Image.open(image_url).convert("RGB")
+
+    # Trimap: prefer trimapBase64 (user-drawn), fall back to trimap URL (from example)
+    if "trimapBase64" in d:
+        b64 = d["trimapBase64"]
+        if "," in b64:
+            b64 = b64.split(",", 1)[1]
+        trimap = PIL.Image.open(BytesIO(base64.b64decode(b64))).convert("L")
+    elif "trimap" in d:
+        trimap = PIL.Image.open(d["trimap"]).convert("L")
+    else:
+        raise gr.Error("Draw a trimap first (mark foreground and unknown regions).")
+
+    return image, trimap
+
+
+def _adjust_background(bg: PIL.Image.Image, target_size: tuple[int, int]) -> PIL.Image.Image:
+    """Crop-resize background to match target dimensions."""
+    tw, th = target_size
+    bw, bh = bg.size
+    scale = max(tw / bw, th / bh)
+    bg = bg.resize((int(bw * scale), int(bh * scale)))
+    left = (bg.width - tw) // 2
+    top = (bg.height - th) // 2
+    return bg.crop((left, top, left + tw, top + th))
+
+
+def _replace_background(
+    image: PIL.Image.Image, alpha: np.ndarray, bg: PIL.Image.Image | None
 ) -> PIL.Image.Image | None:
-    if background_image is None:
+    if bg is None:
         return None
-
-    if image.mode != "RGB":
-        raise gr.Error("Image must be RGB.")
-
-    background_image = background_image.convert("RGB")
-    background_image = adjust_background_image(background_image, image.size)
-
-    image = np.array(image).astype(float) / 255
-    background_image = np.array(background_image).astype(float) / 255
-    result = image * alpha[:, :, None] + background_image * (1 - alpha[:, :, None])
-    return (result * 255).astype(np.uint8)
+    bg = _adjust_background(bg.convert("RGB"), image.size)
+    fg = np.array(image).astype(float) / 255
+    bg_arr = np.array(bg).astype(float) / 255
+    result = fg * alpha[:, :, None] + bg_arr * (1 - alpha[:, :, None])
+    return PIL.Image.fromarray((result * 255).astype(np.uint8))
 
 
 @spaces.GPU
 @torch.inference_mode()
 def run(
-    image: PIL.Image.Image,
-    trimap: PIL.Image.Image,
-    apply_background_replacement: bool,
+    editor_value: str | None,
+    apply_bg: bool,
     background_image: PIL.Image.Image | None,
-) -> tuple[
-    tuple[PIL.Image.Image, np.ndarray],
-    tuple[PIL.Image.Image, PIL.Image.Image],
-    tuple[PIL.Image.Image, PIL.Image.Image] | None,
-]:
-    if image.size != trimap.size:
-        raise gr.Error("Image and trimap must have the same size.")
-    if max(image.size) > MAX_IMAGE_SIZE:
-        error_message = f"Image size is too large. Max image size is {MAX_IMAGE_SIZE} pixels."
-        raise gr.Error(error_message)
-    if image.mode != "RGB":
-        raise gr.Error("Image must be RGB.")
-    if trimap.mode != "L":
-        raise gr.Error("Trimap must be grayscale.")
+) -> tuple:
+    image, trimap = _parse_editor(editor_value)
 
     pixel_values = processor(images=image, trimaps=trimap, return_tensors="pt").to(device).pixel_values
     out = model(pixel_values=pixel_values)
@@ -146,15 +130,14 @@ def run(
     alpha = alpha[:h, :w]
 
     foreground = np.array(image).astype(float) / 255 * alpha[:, :, None] + (1 - alpha[:, :, None])
-    foreground = (foreground * 255).astype(np.uint8)
-    foreground = PIL.Image.fromarray(foreground)
+    foreground = PIL.Image.fromarray((foreground * 255).astype(np.uint8))
 
-    res_bg_replacement = replace_background(image, alpha, background_image) if apply_background_replacement else None
+    res_bg = _replace_background(image, alpha, background_image) if apply_bg else None
 
     return (
         (image, alpha),
         (image, foreground),
-        ((image, res_bg_replacement) if res_bg_replacement is not None else None),
+        (image, res_bg) if res_bg is not None else None,
     )
 
 
@@ -163,49 +146,31 @@ with gr.Blocks(css_paths="style.css") as demo:
 
     with gr.Row():
         with gr.Column():
+            editor = TrimapEditor(label="Image & Trimap")
             with gr.Group():
-                image = gr.Image(label="Input image", type="pil")
-                with gr.Tabs():
-                    with gr.Tab(label="Trimap"):
-                        trimap = gr.Image(label="Trimap", type="pil", image_mode="L")
-                    with gr.Tab(label="Draw trimap"):
-                        mask_editor = gr.ImageEditor(
-                            label="Masks",
-                            type="numpy",
-                            sources=("upload",),
-                            transforms=(),
-                            image_mode="L",
-                            height=500,
-                            brush=gr.Brush(default_color=("#00ff00", 0.6)),
-                            layers=gr.LayerOptions(
-                                allow_additional_layers=False, layers=["Foreground mask", "Unknown mask"]
-                            ),
-                        )
-                        generate_trimap_button = gr.Button("Generate trimap")
-                apply_background_replacement = gr.Checkbox(label="Replace background", value=False)
-                background_image = gr.Image(label="Background image", type="pil", visible=False)
-                run_button = gr.Button("Run")
+                apply_bg = gr.Checkbox(label="Replace background", value=False)
+                bg_image = gr.Image(label="Background image", type="pil", visible=False)
+            run_btn = gr.Button("Run", variant="primary")
         with gr.Column():
-            with gr.Group():
-                out_alpha = gr.ImageSlider(label="Alpha")
-                out_foreground = gr.ImageSlider(label="Foreground")
-                out_background_replacement = gr.ImageSlider(label="Background replacement", visible=False)
-
-    inputs = [
-        image,
-        trimap,
-        apply_background_replacement,
-        background_image,
-    ]
-    outputs = [
-        out_alpha,
-        out_foreground,
-        out_background_replacement,
-    ]
+            out_alpha = gr.ImageSlider(label="Alpha")
+            out_foreground = gr.ImageSlider(label="Foreground")
+            out_bg = gr.ImageSlider(label="Background replacement", visible=False)
+
+    inputs = [editor, apply_bg, bg_image]
+    outputs = [out_alpha, out_foreground, out_bg]
+
     gr.Examples(
         examples=[
-            ["assets/retriever_rgb.png", "assets/retriever_trimap.png", False, None],
-            ["assets/bulb_rgb.png", "assets/bulb_trimap.png", True, "assets/new_bg.jpg"],
+            [
+                [str(_ASSETS_DIR / "retriever_rgb.png"), str(_ASSETS_DIR / "retriever_trimap.png")],
+                False,
+                None,
+            ],
+            [
+                [str(_ASSETS_DIR / "bulb_rgb.png"), str(_ASSETS_DIR / "bulb_trimap.png")],
+                True,
+                str(_ASSETS_DIR / "new_bg.jpg"),
+            ],
         ],
         inputs=inputs,
         outputs=outputs,
@@ -213,35 +178,20 @@ with gr.Blocks(css_paths="style.css") as demo:
         cache_examples=False,
     )
 
-    image.input(
-        fn=resize_input_image,
-        inputs=image,
-        outputs=image,
-        api_name=False,
-    ).then(
-        fn=lambda image: image,
-        inputs=image,
-        outputs=mask_editor,
-        api_name=False,
-    )
-    generate_trimap_button.click(
-        fn=update_trimap,
-        inputs=mask_editor,
-        outputs=trimap,
+    editor.input(
+        fn=_resize_on_upload,
+        inputs=editor,
+        outputs=editor,
         api_name=False,
     )
-    apply_background_replacement.change(
-        fn=lambda checked: (gr.Image(visible=checked), gr.Image(visible=checked)),
-        inputs=apply_background_replacement,
-        outputs=[background_image, out_background_replacement],
+    apply_bg.change(
+        fn=lambda checked: (gr.Image(visible=checked), gr.ImageSlider(visible=checked)),
+        inputs=apply_bg,
+        outputs=[bg_image, out_bg],
         api_name=False,
     )
 
-    run_button.click(
-        fn=run,
-        inputs=inputs,
-        outputs=outputs,
-    )
+    run_btn.click(fn=run, inputs=inputs, outputs=outputs)
 
 if __name__ == "__main__":
     demo.launch()

pyproject.toml

@@ -1,15 +1,15 @@
 [project]
 name = "vitmatte"
 version = "0.1.0"
-description = "Add your description here"
+description = "ViTMatte image matting demo with Trimap Editor"
 readme = "README.md"
-requires-python = ">=3.10"
+requires-python = ">=3.12"
 dependencies = [
-    "gradio>=5.39.0",
-    "hf-transfer>=0.1.9",
-    "spaces>=0.39.0",
-    "torch==2.5.1",
-    "transformers>=4.54.1",
+    "gradio>=6.8.0",
+    "spaces>=0.47.0",
+    "torch==2.9.1",
+    "transformers>=5.2.0",
+    "trimap-editor",
 ]
 
 [tool.ruff]
@@ -34,7 +34,6 @@ ignore = [
     "EM101",   # raw-string-in-exception
     "FBT001",  # boolean-type-hint-positional-argument
     "FBT002",  # boolean-default-value-positional-argument
-    "PD901",   # pandas-df-variable-name
     "PGH003",  # blanket-type-ignore
     "PLR0913", # too-many-arguments
     "PLR0915", # too-many-statements
@@ -47,8 +46,17 @@ unfixable = [
 [tool.ruff.lint.pydocstyle]
 convention = "google"
 
-[tool.ruff.lint.per-file-ignores]
-"*.ipynb" = ["T201", "T203"]
-
 [tool.ruff.format]
 docstring-code-format = true
+
+[tool.uv.sources]
+trimap-editor = { url = "https://github.com/hysts/gradio-trimap-editor/releases/download/v0.1.0/trimap_editor-0.1.0-py3-none-any.whl" }
+
+[dependency-groups]
+dev = [
+    "pre-commit>=4.5.1",
+    "ruff>=0.15.4",
+]
+hf-spaces = [
+    "datasets>=4.6.0",
+]

requirements.txt

@@ -1,49 +1,75 @@
 # This file was autogenerated by uv via the following command:
-#    uv pip compile pyproject.toml -o requirements.txt
+#    uv export --no-hashes --group hf-spaces --no-emit-package typer-slim -o requirements.txt
 aiofiles==24.1.0
     # via gradio
+aiohappyeyeballs==2.6.1
+    # via aiohttp
+aiohttp==3.13.3
+    # via fsspec
+aiosignal==1.4.0
+    # via aiohttp
+annotated-doc==0.0.4
+    # via
+    #   fastapi
+    #   typer
 annotated-types==0.7.0
     # via pydantic
-anyio==4.9.0
+anyio==4.12.1
     # via
     #   gradio
     #   httpx
     #   starlette
-brotli==1.1.0
+attrs==25.4.0
+    # via aiohttp
+audioop-lts==0.2.2 ; python_full_version >= '3.13'
     # via gradio
-certifi==2025.8.3
+brotli==1.2.0
+    # via gradio
+certifi==2026.2.25
     # via
     #   httpcore
     #   httpx
     #   requests
-charset-normalizer==3.4.2
+charset-normalizer==3.4.4
     # via requests
-click==8.2.1
+click==8.3.1
     # via
     #   typer
     #   uvicorn
-exceptiongroup==1.3.0
-    # via anyio
-fastapi==0.116.1
+colorama==0.4.6 ; sys_platform == 'win32'
+    # via
+    #   click
+    #   tqdm
+datasets==4.6.1
+dill==0.4.0
+    # via
+    #   datasets
+    #   multiprocess
+fastapi==0.134.0
     # via gradio
-ffmpy==0.6.1
+ffmpy==1.0.0
     # via gradio
-filelock==3.18.0
+filelock==3.24.3
     # via
+    #   datasets
     #   huggingface-hub
     #   torch
-    #   transformers
-    #   triton
-fsspec==2025.7.0
+frozenlist==1.8.0
     # via
+    #   aiohttp
+    #   aiosignal
+fsspec==2026.2.0
+    # via
+    #   datasets
     #   gradio-client
     #   huggingface-hub
     #   torch
-gradio==5.39.0
+gradio==6.8.0
     # via
-    #   vitmatte (pyproject.toml)
     #   spaces
-gradio-client==1.11.0
+    #   trimap-editor
+    #   vitmatte
+gradio-client==2.2.0
     # via gradio
 groovy==0.1.2
     # via gradio
@@ -51,36 +77,38 @@ h11==0.16.0
     # via
     #   httpcore
     #   uvicorn
-hf-transfer==0.1.9
-    # via vitmatte (pyproject.toml)
-hf-xet==1.1.5
+hf-xet==1.3.2 ; platform_machine == 'AMD64' or platform_machine == 'aarch64' or platform_machine == 'amd64' or platform_machine == 'arm64' or platform_machine == 'x86_64'
     # via huggingface-hub
 httpcore==1.0.9
     # via httpx
 httpx==0.28.1
     # via
+    #   datasets
     #   gradio
     #   gradio-client
+    #   huggingface-hub
     #   safehttpx
     #   spaces
-huggingface-hub==0.34.3
+huggingface-hub==1.5.0
     # via
+    #   datasets
     #   gradio
     #   gradio-client
     #   tokenizers
     #   transformers
-idna==3.10
+idna==3.11
     # via
     #   anyio
     #   httpx
     #   requests
+    #   yarl
 jinja2==3.1.6
     # via
     #   gradio
     #   torch
-markdown-it-py==3.0.0
+markdown-it-py==4.0.0
     # via rich
-markupsafe==3.0.2
+markupsafe==3.0.3
     # via
     #   gradio
     #   jinja2
@@ -88,66 +116,91 @@ mdurl==0.1.2
     # via markdown-it-py
 mpmath==1.3.0
     # via sympy
-networkx==3.4.2
+multidict==6.7.1
+    # via
+    #   aiohttp
+    #   yarl
+multiprocess==0.70.18
+    # via datasets
+networkx==3.6.1
     # via torch
-numpy==2.2.6
+numpy==2.4.2
     # via
+    #   datasets
     #   gradio
     #   pandas
     #   transformers
-nvidia-cublas-cu12==12.4.5.8
+nvidia-cublas-cu12==12.8.4.1 ; platform_machine == 'x86_64' and sys_platform == 'linux'
     # via
     #   nvidia-cudnn-cu12
     #   nvidia-cusolver-cu12
     #   torch
-nvidia-cuda-cupti-cu12==12.4.127
+nvidia-cuda-cupti-cu12==12.8.90 ; platform_machine == 'x86_64' and sys_platform == 'linux'
+    # via torch
+nvidia-cuda-nvrtc-cu12==12.8.93 ; platform_machine == 'x86_64' and sys_platform == 'linux'
     # via torch
-nvidia-cuda-nvrtc-cu12==12.4.127
+nvidia-cuda-runtime-cu12==12.8.90 ; platform_machine == 'x86_64' and sys_platform == 'linux'
     # via torch
-nvidia-cuda-runtime-cu12==12.4.127
+nvidia-cudnn-cu12==9.10.2.21 ; platform_machine == 'x86_64' and sys_platform == 'linux'
     # via torch
-nvidia-cudnn-cu12==9.1.0.70
+nvidia-cufft-cu12==11.3.3.83 ; platform_machine == 'x86_64' and sys_platform == 'linux'
     # via torch
-nvidia-cufft-cu12==11.2.1.3
+nvidia-cufile-cu12==1.13.1.3 ; platform_machine == 'x86_64' and sys_platform == 'linux'
     # via torch
-nvidia-curand-cu12==10.3.5.147
+nvidia-curand-cu12==10.3.9.90 ; platform_machine == 'x86_64' and sys_platform == 'linux'
     # via torch
-nvidia-cusolver-cu12==11.6.1.9
+nvidia-cusolver-cu12==11.7.3.90 ; platform_machine == 'x86_64' and sys_platform == 'linux'
     # via torch
-nvidia-cusparse-cu12==12.3.1.170
+nvidia-cusparse-cu12==12.5.8.93 ; platform_machine == 'x86_64' and sys_platform == 'linux'
     # via
     #   nvidia-cusolver-cu12
     #   torch
-nvidia-nccl-cu12==2.21.5
+nvidia-cusparselt-cu12==0.7.1 ; platform_machine == 'x86_64' and sys_platform == 'linux'
+    # via torch
+nvidia-nccl-cu12==2.27.5 ; platform_machine == 'x86_64' and sys_platform == 'linux'
     # via torch
-nvidia-nvjitlink-cu12==12.4.127
+nvidia-nvjitlink-cu12==12.8.93 ; platform_machine == 'x86_64' and sys_platform == 'linux'
     # via
+    #   nvidia-cufft-cu12
     #   nvidia-cusolver-cu12
     #   nvidia-cusparse-cu12
     #   torch
-nvidia-nvtx-cu12==12.4.127
+nvidia-nvshmem-cu12==3.3.20 ; platform_machine == 'x86_64' and sys_platform == 'linux'
     # via torch
-orjson==3.11.1
+nvidia-nvtx-cu12==12.8.90 ; platform_machine == 'x86_64' and sys_platform == 'linux'
+    # via torch
+orjson==3.11.7
     # via gradio
-packaging==25.0
+packaging==26.0
     # via
+    #   datasets
     #   gradio
     #   gradio-client
     #   huggingface-hub
     #   spaces
     #   transformers
-pandas==2.3.1
-    # via gradio
-pillow==11.3.0
-    # via gradio
+pandas==3.0.1
+    # via
+    #   datasets
+    #   gradio
+pillow==12.1.1
+    # via
+    #   gradio
+    #   trimap-editor
+propcache==0.4.1
+    # via
+    #   aiohttp
+    #   yarl
 psutil==5.9.8
     # via spaces
-pydantic==2.11.7
+pyarrow==23.0.1
+    # via datasets
+pydantic==2.12.5
     # via
     #   fastapi
     #   gradio
     #   spaces
-pydantic-core==2.33.2
+pydantic-core==2.41.5
     # via pydantic
 pydub==0.25.1
     # via gradio
@@ -155,66 +208,71 @@ pygments==2.19.2
     # via rich
 python-dateutil==2.9.0.post0
     # via pandas
-python-multipart==0.0.20
+python-multipart==0.0.22
     # via gradio
 pytz==2025.2
-    # via pandas
-pyyaml==6.0.2
+    # via gradio
+pyyaml==6.0.3
     # via
+    #   datasets
     #   gradio
     #   huggingface-hub
     #   transformers
-regex==2025.7.34
+regex==2026.2.28
     # via transformers
-requests==2.32.4
+requests==2.32.5
     # via
-    #   huggingface-hub
+    #   datasets
     #   spaces
-    #   transformers
-rich==14.1.0
+rich==14.3.3
     # via typer
-ruff==0.12.7
-    # via gradio
-safehttpx==0.1.6
+ruff==0.15.4
+safehttpx==0.1.7
     # via gradio
-safetensors==0.5.3
+safetensors==0.7.0
     # via transformers
 semantic-version==2.10.0
     # via gradio
+setuptools==82.0.0
+    # via torch
 shellingham==1.5.4
     # via typer
 six==1.17.0
     # via python-dateutil
-sniffio==1.3.1
-    # via anyio
-spaces==0.39.0
-    # via vitmatte (pyproject.toml)
-starlette==0.47.2
+spaces==0.47.0
+    # via vitmatte
+starlette==0.52.1
     # via
     #   fastapi
     #   gradio
-sympy==1.13.1
+sympy==1.14.0
     # via torch
-tokenizers==0.21.4
+tokenizers==0.22.2
     # via transformers
 tomlkit==0.13.3
     # via gradio
-torch==2.5.1
-    # via vitmatte (pyproject.toml)
-tqdm==4.67.1
+torch==2.9.1
+    # via vitmatte
+tqdm==4.67.3
     # via
+    #   datasets
     #   huggingface-hub
     #   transformers
-transformers==4.54.1
-    # via vitmatte (pyproject.toml)
-triton==3.1.0
+transformers==5.2.0
+    # via vitmatte
+trimap-editor @ https://github.com/hysts/gradio-trimap-editor/releases/download/v0.1.0/trimap_editor-0.1.0-py3-none-any.whl
+    # via vitmatte
+triton==3.5.1 ; platform_machine == 'x86_64' and sys_platform == 'linux'
     # via torch
-typer==0.16.0
-    # via gradio
-typing-extensions==4.14.1
+typer==0.24.1
     # via
+    #   gradio
+    #   huggingface-hub
+    #   typer-slim
+typing-extensions==4.15.0
+    # via
+    #   aiosignal
     #   anyio
-    #   exceptiongroup
     #   fastapi
     #   gradio
     #   gradio-client
@@ -224,16 +282,18 @@ typing-extensions==4.14.1
     #   spaces
     #   starlette
     #   torch
-    #   typer
     #   typing-inspection
-    #   uvicorn
-typing-inspection==0.4.1
-    # via pydantic
-tzdata==2025.2
+typing-inspection==0.4.2
+    # via
+    #   fastapi
+    #   pydantic
+tzdata==2025.3 ; sys_platform == 'emscripten' or sys_platform == 'win32'
     # via pandas
-urllib3==2.5.0
+urllib3==2.6.3
     # via requests
-uvicorn==0.35.0
+uvicorn==0.41.0
     # via gradio
-websockets==15.0.1
-    # via gradio-client
+xxhash==3.6.0
+    # via datasets
+yarl==1.22.0
+    # via aiohttp