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app.py
CHANGED
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@@ -7,13 +7,15 @@ import json
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from datasets import load_dataset
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from flask import Flask
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from flask_cors import CORS
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app = Flask(__name__, static_url_path='/static')
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CORS(app)
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TOKEN = os.environ.get('dataset_token')
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dataset = load_dataset(
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Path("static/images").mkdir(parents=True, exist_ok=True)
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# extract images and prompts from dataset and save to dis
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@@ -22,8 +24,9 @@ for row in dataset['train']:
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prompt = dataset['train'].features['label'].int2str(row['label'])
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image = row['image']
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hash = uuid.uuid4().hex
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image_file = Path(f'static/images/{hash}.
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image.
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if prompt not in data:
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data[prompt] = []
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data[prompt].append(str(image_file))
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@@ -36,6 +39,7 @@ with open('static/data.json', 'w') as f:
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def index():
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return app.send_static_file('index.html')
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@app.route('/data')
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def getdata():
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return app.send_static_file('data.json')
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from datasets import load_dataset
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from flask import Flask
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from flask_cors import CORS
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from PIL import Image
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app = Flask(__name__, static_url_path='/static')
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CORS(app)
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TOKEN = os.environ.get('dataset_token')
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dataset = load_dataset(
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"huggingface-projects/wordalle_prompts", use_auth_token=TOKEN)
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Path("static/images").mkdir(parents=True, exist_ok=True)
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# extract images and prompts from dataset and save to dis
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prompt = dataset['train'].features['label'].int2str(row['label'])
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image = row['image']
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hash = uuid.uuid4().hex
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image_file = Path(f'static/images/{hash}.jpg')
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image_compress = image.resize((136, 136), Image.Resampling.LANCZOS)
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image_compress.save(image_file, optimize=True, quality=95)
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if prompt not in data:
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data[prompt] = []
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data[prompt].append(str(image_file))
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def index():
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return app.send_static_file('index.html')
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@app.route('/data')
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def getdata():
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return app.send_static_file('data.json')
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