Upload 6 files

app.py

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+import fn
+import gradio as gr
+
+fn.load_model()
+
+with gr.Blocks() as demo:
+    title = gr.Markdown('# Safety Checker')
+    with gr.Row():
+        src_image = gr.Image(label="Source", sources="upload", interactive=True, type="pil")
+        result = gr.Textbox(label="Result", interactive=False)
+
+    src_image.change(
+        fn=fn.check,
+        inputs=[src_image],
+        outputs=[result],
+    )
+
+if __name__ == '__main__':
+    demo.launch()

fn.py

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+from diffusers.pipelines.stable_diffusion import StableDiffusionSafetyChecker
+from transformers import CLIPFeatureExtractor
+import numpy as np
+import torch
+from PIL import Image 
+from typing import Optional, Tuple, Union
+
+device = None
+torch_device = None
+torch_dtype = None
+safety_checker = None
+feature_extractor = None
+
+def load_model():
+    global device, torch_device, torch_dtype, safety_checker, feature_extractor
+
+    device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+    torch_device = device
+    torch_dtype = torch.float16
+
+    safety_checker = StableDiffusionSafetyChecker.from_pretrained(
+        "CompVis/stable-diffusion-safety-checker"
+    ).to(device)
+    feature_extractor = CLIPFeatureExtractor.from_pretrained(
+        "openai/clip-vit-base-patch32"
+    )
+
+def check(image):
+    images = [image]
+    safety_checker_input = feature_extractor(images, return_tensors="pt").to(device)
+    images_np = [np.array(img) for img in images]
+
+    _, has_nsfw_concepts = safety_checker(
+        images=images_np,
+        clip_input=safety_checker_input.pixel_values.to(torch_device),
+    )
+
+    return has_nsfw_concepts[0]

install.bat

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+@echo off
+
+rem -------------------------------------------
+rem NOT guaranteed to work on Windows
+
+set REPOS=https://huggingface.co/spaces/aka7774/safetychecker
+set APPDIR=safetychecker
+set VENV=venv
+
+rem -------------------------------------------
+
+set INSTALL_DIR=%~dp0
+cd /d %INSTALL_DIR%
+
+:git_clone
+set DL_URL=%REPOS%
+set DL_DST=%APPDIR%
+git clone %DL_URL% %APPDIR%
+if exist %DL_DST% goto install_python
+
+set DL_URL=https://github.com/git-for-windows/git/releases/download/v2.41.0.windows.3/PortableGit-2.41.0.3-64-bit.7z.exe
+set DL_DST=PortableGit-2.41.0.3-64-bit.7z.exe
+curl -L -o %DL_DST% %DL_URL%
+if not exist %DL_DST% bitsadmin /transfer dl %DL_URL% %DL_DST%
+%DL_DST% -y
+del %DL_DST%
+
+set GIT=%INSTALL_DIR%PortableGit\bin\git
+%GIT% clone %REPOS%
+
+:install_python
+set DL_URL=https://github.com/indygreg/python-build-standalone/releases/download/20240107/cpython-3.10.13+20240107-i686-pc-windows-msvc-shared-install_only.tar.gz
+set DL_DST="%INSTALL_DIR%python.tar.gz"
+curl -L -o %DL_DST% %DL_URL%
+if not exist %DL_DST% bitsadmin /transfer dl %DL_URL% %DL_DST%
+tar -xzf %DL_DST%
+
+set PYTHON=%INSTALL_DIR%python\python.exe
+set PATH=%PATH%;%INSTALL_DIR%python310\Scripts
+
+:install_venv
+cd %APPDIR%
+%PYTHON% -m venv %VENV%
+set PYTHON=%VENV%\Scripts\python.exe
+
+:install_pip
+set DL_URL=https://bootstrap.pypa.io/get-pip.py
+set DL_DST=%INSTALL_DIR%get-pip.py
+curl -o %DL_DST% %DL_URL%
+if not exist %DL_DST% bitsadmin /transfer dl %DL_URL% %DL_DST%
+%PYTHON% %DL_DST%
+
+%PYTHON% -m pip install gradio
+%PYTHON% -m pip install -r requirements.txt
+
+pause

main.py

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+import os
+import sys
+import time
+import signal
+import io
+from PIL import Image
+
+from fastapi import FastAPI, Request, status, Form, UploadFile
+from fastapi.staticfiles import StaticFiles
+from fastapi.middleware.cors import CORSMiddleware
+from pydantic import BaseModel, Field
+from fastapi.exceptions import RequestValidationError
+from fastapi.responses import Response
+
+import fn
+import gradio as gr
+from app import demo
+
+app = FastAPI()
+
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=['*'],
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+gr.mount_gradio_app(app, demo, path="/gradio")
+
+fn.load_model()
+
+@app.post("/check")
+async def check_image(file: UploadFile = Form(...)):
+    file_content = await file.read()
+    file_stream = io.BytesIO(file_content)
+
+    result = fn.check(Image.open(file_stream))
+
+    return {"has_nsfw": result}
+    

requirements.txt

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+fastapi
+uvicorn
+torch
+diffusers
+transformers
+numpy
+python-multipart

venv.sh

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+#!/usr/bin/bash
+
+python3 -m venv venv
+curl -kL https://bootstrap.pypa.io/get-pip.py | venv/bin/python
+
+venv/bin/python -m pip install gradio
+venv/bin/python -m pip install -r requirements.txt