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import os
import torch
import gradio as gr
from depth_anything_3.model import DepthAnything3
# ---------------------------------------------------------
# CPU-safe DepthAnything3 loader
# ---------------------------------------------------------
def load_model_cpu(model_dir):
print("🔄 Loading DepthAnything3 model on CPU...")
model = DepthAnything3.from_pretrained(model_dir, config_name="config.json")
model.to("cpu")
model.eval()
print("✅ Model ready on CPU")
return model
MODEL_DIR = os.environ.get("DA3_MODEL_DIR", "depth-anything/DA3NESTED-GIANT-LARGE")
model = load_model_cpu(MODEL_DIR)
# ---------------------------------------------------------
# CPU-safe inference (single image only)
# ---------------------------------------------------------
def run_depth(img):
"""
CPU version of depth inference.
No batching, no multiview, no GS, no reconstruction.
"""
if img is None:
return None
with torch.no_grad():
depth = model.infer_image(img, device="cpu")
return depth
# ---------------------------------------------------------
# Minimal Gradio UI (fast startup)
# ---------------------------------------------------------
title = "Depth Anything 3 — CPU Mode (Safe HF Version)"
description = """
This Hugging Face Space runs **DepthAnything3** in CPU-only mode.
Only single-image depth inference is enabled.
All heavy multiview / GS / reconstruction features were removed so the Space can boot on CPU.
"""
demo = gr.Interface(
fn=run_depth,
inputs=gr.Image(type="pil", label="Upload an image"),
outputs=gr.Image(label="Predicted Depth"),
title=title,
description=description,
)
if __name__ == "__main__":
demo.launch(server_name="0.0.0.0", server_port=7860)
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