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Browse files- Dockerfile +15 -0
- app.py +75 -0
- requirements.txt +58 -0
Dockerfile
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FROM python:3.9
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WORKDIR /code
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# Create cache directory and set permissions
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RUN mkdir -p /.cache/huggingface/hub && \
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chmod -R 777 /.cache
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COPY ./requirements.txt /code/requirements.txt
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RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt
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COPY . .
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CMD ["gunicorn","-b", "0.0.0.0:7860", "app:app"]
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app.py
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import os
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from transformers import AutoModelForImageClassification, AutoFeatureExtractor
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import torch
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from flask_cors import CORS
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from flask import Flask, request, json
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from PIL import Image
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import requests
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from io import BytesIO
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from bs4 import BeautifulSoup
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from urllib.parse import urljoin
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os.environ["CUDA_VISIBLE_DEVICES"] = ""
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app = Flask(__name__)
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cors = CORS(app)
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# Define the model and feature extractor globally
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model = AutoModelForImageClassification.from_pretrained('carbon225/vit-base-patch16-224-hentai')
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feature_extractor = AutoFeatureExtractor.from_pretrained('carbon225/vit-base-patch16-224-hentai')
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@app.route("/", methods=["GET"])
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def default():
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return json.dumps({"Server": "Working"})
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@app.route("/extractimages",methods=["GET"])
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def extract_images():
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try:
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src=request.args.get("src")
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response = requests.get(src)
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soup = BeautifulSoup(response.content,'html.parser')
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img_urls=[]
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img_tags = soup.select('div img')
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for img_tag in img_tags:
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img_url = urljoin(src, img_tag['src'])
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img_urls.append(img_url)
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return json.dumps({"images":img_urls})
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except Exception as e:
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return e
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@app.route("/predict", methods=["GET"])
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def predict():
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try:
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src = request.args.get("src")
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# Download image from the provided URL
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response = requests.get(src)
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response.raise_for_status()
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# Open and preprocess the image
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image = Image.open(BytesIO(response.content))
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image = image.resize((128, 128))
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# Extract features using the pre-trained feature extractor
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encoding = feature_extractor(images=image.convert("RGB"), return_tensors="pt")
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# Make a prediction using the pre-trained model
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with torch.no_grad():
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outputs = model(**encoding)
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logits = outputs.logits
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# Get the predicted class index and label
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predicted_class_idx = logits.argmax(-1).item()
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predicted_class_label = model.config.id2label[predicted_class_idx]
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# Return the predictions
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return json.dumps({"class": predicted_class_label})
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except requests.exceptions.RequestException as e:
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return json.dumps({"error": f"Request error: {str(e)}"})
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except Exception as e:
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return json.dumps({"error": f"An unexpected error occurred: {str(e)}"})
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if __name__ == "__main__":
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app.run(debug=True)
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requirements.txt
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blinker==1.7.0
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bs4==0.0.1
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certifi==2023.11.17
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charset-normalizer==3.3.2
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click==8.1.7
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filelock==3.13.1
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Flask==3.0.0
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Flask-Cors==4.0.0
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fsspec==2023.12.2
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huggingface-hub==0.20.1
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idna==3.6
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importlib-metadata==7.0.0
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itsdangerous==2.1.2
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Jinja2==3.1.2
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markdownify==0.11.6
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MarkupSafe==2.1.3
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mpmath==1.3.0
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networkx==3.2.1
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numpy==1.26.2
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nvidia-cublas-cu12==12.1.3.1
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nvidia-cuda-cupti-cu12==12.1.105
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nvidia-cuda-nvrtc-cu12==12.1.105
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nvidia-cuda-runtime-cu12==12.1.105
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nvidia-cudnn-cu12==8.9.2.26
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nvidia-cufft-cu12==11.0.2.54
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nvidia-curand-cu12==10.3.2.106
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nvidia-cusolver-cu12==11.4.5.107
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nvidia-cusparse-cu12==12.1.0.106
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nvidia-nccl-cu12==2.18.1
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nvidia-nvjitlink-cu12==12.3.101
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nvidia-nvtx-cu12==12.1.105
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outcome==1.2.0
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packaging==23.2
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perplexity-api @ git+https://gitlab.com/robowaifudev/perplexity-api@0baebed39beeedc13e6281af5505f4c4221fdb5f
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Pillow==10.1.0
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PySocks==1.7.1
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PyYAML==6.0.1
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regex==2023.10.3
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requests==2.31.0
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safetensors==0.4.1
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selenium==4.12.0
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sortedcontainers==2.4.0
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sympy==1.12
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tokenizers==0.15.0
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torch==2.1.2
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tqdm==4.66.1
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transformers==4.36.2
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trio==0.22.2
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trio-websocket==0.10.4
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triton==2.1.0
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typing_extensions==4.9.0
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urllib3==2.1.0
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Werkzeug==3.0.1
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wsproto==1.2.0
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zipp==3.17.0
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gunicorn
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torch
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bs4
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