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import os
import torch
from flask import Flask, request, jsonify, send_file
from pipeline import Zero123PlusPipeline # from your local pipeline.py
from PIL import Image
from io import BytesIO
app = Flask(__name__)
# Load the model once at startup (on CPU)
print("Loading Zero123Plus pipeline on CPU...")
pipe = Zero123PlusPipeline.from_pretrained(
"sudo-ai/zero123plus-v1.2",
torch_dtype=torch.float32,
)
pipe.to("cpu")
pipe.enable_model_cpu_offload()
print("Model loaded.")
@app.route("/")
def home():
return '''
<h1>Zero123Plus Image to 3D Generator</h1>
<form action="/generate" method="post" enctype="multipart/form-data">
<p>Upload a single-view image:</p>
<input type="file" name="image"><br><br>
<input type="submit" value="Generate 3D View">
</form>
'''
@app.route("/generate", methods=["POST"])
def generate():
if "image" not in request.files:
return jsonify({"error": "No image uploaded"}), 400
file = request.files["image"]
image = Image.open(file.stream).convert("RGB")
print("Generating 3D view...")
result = pipe(image, num_inference_steps=50, guidance_scale=3.0)
output = result.images[0]
img_io = BytesIO()
output.save(img_io, "PNG")
img_io.seek(0)
return send_file(img_io, mimetype="image/png")
if __name__ == "__main__":
app.run(host="0.0.0.0", port=7860) |