app.py

app.py

@@ -0,0 +1,54 @@
+from flask import Flask, render_template, request, send_file
+from PIL import Image
+import io
+
+app = Flask(__name__)
+
+# Load the pre-trained GPT-2 model and tokenizer
+from transformers import AutoTokenizer, AutoModel
+
+tokenizer = AutoTokenizer.from_pretrained("EleutherAI/gpt-neo-2.7B")
+model = AutoModel.from_pretrained("EleutherAI/gpt-neo-2.7B")
+
+# Define a function to generate images from model output
+from PIL import Image, ImageDraw, ImageFont
+import numpy as np
+
+def generate_image(text):
+    # Generate model output
+    input_ids = tokenizer.encode(text, return_tensors="pt")
+    output = model.generate(input_ids)
+
+    # Convert output to image
+    image_array = output[0].numpy().transpose(1, 2, 0)
+    image_array = ((image_array + 1) / 2.0) * 255.0
+    image_array = image_array.astype(np.uint8)
+    image = Image.fromarray(image_array)
+
+    # Add text to image
+    draw = ImageDraw.Draw(image)
+    font = ImageFont.truetype("arial.ttf", size=50)
+    draw.text((50, 50), text, font=font, fill=(0, 0, 0))
+
+    return image
+
+# Define a route to handle the form submission
+@app.route('/', methods=['GET', 'POST'])
+def text_to_image():
+    if request.method == 'POST':
+        # Get text input from user
+        text = request.form['text']
+
+        # Generate image from text
+        image = generate_image(text)
+
+        # Return image to user
+        img_io = io.BytesIO()
+        image.save(img_io, 'JPEG')
+        img_io.seek(0)
+        return send_file(img_io, mimetype='image/jpeg')
+    else:
+        return render_template('index.html')
+
+if __name__ == '__main__':
+    app.run()