Upload external/MV-Adapter/scripts/gradio_demo_t2mv.py with huggingface_hub

external/MV-Adapter/scripts/gradio_demo_t2mv.py

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+import argparse
+import random
+
+import gradio as gr
+import numpy as np
+
+# import spaces
+import torch
+
+from .inference_t2mv_sdxl import prepare_pipeline, run_pipeline
+
+# Base model
+parser = argparse.ArgumentParser()
+parser.add_argument(
+    "--base_model", type=str, default="stabilityai/stable-diffusion-xl-base-1.0"
+)
+parser.add_argument("--scheduler", type=str, default=None)
+args = parser.parse_args()
+base_model = args.base_model
+scheduler = args.scheduler
+
+# Device and dtype
+dtype = torch.bfloat16
+device = "cuda" if torch.cuda.is_available() else "cpu"
+
+# Hyperparameters
+NUM_VIEWS = 6
+HEIGHT = 768
+WIDTH = 768
+MAX_SEED = np.iinfo(np.int32).max
+
+pipe = prepare_pipeline(
+    base_model=base_model,
+    vae_model="madebyollin/sdxl-vae-fp16-fix",
+    unet_model=None,
+    lora_model=None,
+    adapter_path="huanngzh/mv-adapter",
+    scheduler=scheduler,
+    num_views=NUM_VIEWS,
+    device=device,
+    dtype=dtype,
+)
+
+
+# @spaces.GPU()
+def infer(
+    prompt,
+    seed=42,
+    randomize_seed=False,
+    guidance_scale=7.0,
+    num_inference_steps=50,
+    negative_prompt="watermark, ugly, deformed, noisy, blurry, low contrast",
+    progress=gr.Progress(track_tqdm=True),
+):
+    if randomize_seed:
+        seed = random.randint(0, MAX_SEED)
+    images = run_pipeline(
+        pipe,
+        num_views=NUM_VIEWS,
+        text=prompt,
+        height=HEIGHT,
+        width=WIDTH,
+        num_inference_steps=num_inference_steps,
+        guidance_scale=guidance_scale,
+        seed=seed,
+        negative_prompt=negative_prompt,
+        device=device,
+    )
+    return images, seed
+
+
+examples = {
+    "stabilityai/stable-diffusion-xl-base-1.0": [
+        ["An astronaut riding a horse", 42],
+        ["A DSLR photo of a frog wearing a sweater", 42],
+    ],
+    "cagliostrolab/animagine-xl-3.1": [
+        [
+            "1girl, izayoi sakuya, touhou, solo, maid headdress, maid, apron, short sleeves, dress, closed mouth, white apron, serious face, upper body, masterpiece, best quality, very aesthetic, absurdres",
+            0,
+        ],
+        [
+            "1boy, male focus, ikari shinji, neon genesis evangelion, solo, serious face,(masterpiece), (best quality), (ultra-detailed), very aesthetic, illustration, disheveled hair, moist skin, intricate details",
+            0,
+        ],
+        [
+            "1girl, pink hair, pink shirts, smile, shy, masterpiece, anime",
+            0,
+        ],
+    ],
+    "Lykon/dreamshaper-xl-1-0": [
+        ["the warrior Aragorn from Lord of the Rings, film grain, 8k hd", 0],
+        [
+            "Oil painting, masterpiece, regal, fancy.  A well-dressed dog named Puproy Doggerson III wearing reading glasses types an important letter on a typewriter and enjoys a cup of coffee with the newspaper.",
+            42,
+        ],
+    ],
+}
+
+css = """
+#col-container {
+    margin: 0 auto;
+    max-width: 600px;
+}
+"""
+
+with gr.Blocks(css=css) as demo:
+
+    with gr.Column(elem_id="col-container"):
+        gr.Markdown(
+            f"""# MV-Adapter [Text-to-Multi-View]
+Generate 768x768 multi-view images using {base_model} <br>
+[[page](https://huanngzh.github.io/MV-Adapter-Page/)] [[repo](https://github.com/huanngzh/MV-Adapter)]
+        """
+        )
+
+        with gr.Row():
+            prompt = gr.Text(
+                label="Prompt",
+                show_label=False,
+                max_lines=1,
+                placeholder="Enter your prompt",
+                container=False,
+            )
+
+            run_button = gr.Button("Run", scale=0)
+
+        result = gr.Gallery(
+            label="Result",
+            show_label=False,
+            columns=[3],
+            rows=[2],
+            object_fit="contain",
+            height="auto",
+        )
+
+        with gr.Accordion("Advanced Settings", open=False):
+            seed = gr.Slider(
+                label="Seed",
+                minimum=0,
+                maximum=MAX_SEED,
+                step=1,
+                value=0,
+            )
+            randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
+
+            with gr.Row():
+                num_inference_steps = gr.Slider(
+                    label="Number of inference steps",
+                    minimum=1,
+                    maximum=50,
+                    step=1,
+                    value=50,
+                )
+
+            with gr.Row():
+                guidance_scale = gr.Slider(
+                    label="CFG scale",
+                    minimum=0.0,
+                    maximum=10.0,
+                    step=0.1,
+                    value=7.0,
+                )
+
+            with gr.Row():
+                negative_prompt = gr.Textbox(
+                    label="Negative prompt",
+                    placeholder="Enter your negative prompt",
+                    value="watermark, ugly, deformed, noisy, blurry, low contrast",
+                )
+
+        if base_model in examples:
+            gr.Examples(
+                examples=examples[base_model],
+                fn=infer,
+                inputs=[prompt, seed],
+                outputs=[result, seed],
+                cache_examples=True,
+            )
+
+    gr.on(
+        triggers=[run_button.click, prompt.submit],
+        fn=infer,
+        inputs=[
+            prompt,
+            seed,
+            randomize_seed,
+            guidance_scale,
+            num_inference_steps,
+            negative_prompt,
+        ],
+        outputs=[result, seed],
+    )
+
+demo.launch()