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| from functools import partial | |
| from PIL import Image | |
| import numpy as np | |
| import gradio as gr | |
| import torch | |
| import os | |
| import fire | |
| from ldm.util import add_margin | |
| _TITLE = '''SyncDreamer: Generating Multiview-consistent Images from a Single-view Image''' | |
| _DESCRIPTION = ''' | |
| <div> | |
| <a style="display:inline-block" href="https://liuyuan-pal.github.io/SyncDreamer/"><img src="https://img.shields.io/badge/SyncDremer-Homepage-blue"></a> | |
| <a style="display:inline-block; margin-left: .5em" href="https://arxiv.org/abs/2309.03453"><img src="https://img.shields.io/badge/2309.03453-f9f7f7?logo=data:image/png;base64,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"></a> | |
| <a style="display:inline-block; margin-left: .5em" href='https://github.com/liuyuan-pal/SyncDreamer'><img src='https://img.shields.io/github/stars/liuyuan-pal/SyncDreamer?style=social' /></a> | |
| </div> | |
| Given a single-view image, SyncDreamer is able to generate multiview-consistent images, which enables direct 3D reconstruction with NeuS or NeRF without SDS loss''' | |
| _USER_GUIDE0 = "Step0: Please upload an image in the block above (or choose an example above). We use alpha values as object masks if given." | |
| _USER_GUIDE1 = "Step1: Please select a crop size using the glider." | |
| _USER_GUIDE2 = "Step2: Please choose a suitable elevation angle and then click the Generate button." | |
| def mask_prediction(mask_predictor, image_in: Image.Image): | |
| if image_in.mode=='RGBA': | |
| return image_in | |
| else: | |
| raise NotImplementedError | |
| def resize_inputs(image_input, crop_size): | |
| alpha_np = np.asarray(image_input)[:, :, 3] | |
| coords = np.stack(np.nonzero(alpha_np), 1)[:, (1, 0)] | |
| min_x, min_y = np.min(coords, 0) | |
| max_x, max_y = np.max(coords, 0) | |
| ref_img_ = image_input.crop((min_x, min_y, max_x, max_y)) | |
| h, w = ref_img_.height, ref_img_.width | |
| scale = crop_size / max(h, w) | |
| h_, w_ = int(scale * h), int(scale * w) | |
| ref_img_ = ref_img_.resize((w_, h_), resample=Image.BICUBIC) | |
| results = add_margin(ref_img_, size=256) | |
| return results | |
| def run_demo(): | |
| device = f"cuda:0" if torch.cuda.is_available() else "cpu" | |
| models = None # init_model(device, os.path.join(code_dir, ckpt)) | |
| # init sam model | |
| mask_predictor = None # sam_init(device_idx) | |
| # with open('instructions_12345.md', 'r') as f: | |
| # article = f.read() | |
| # NOTE: Examples must match inputs | |
| example_folder = os.path.join(os.path.dirname(__file__), 'hf_demo', 'examples') | |
| example_fns = os.listdir(example_folder) | |
| example_fns.sort() | |
| examples_full = [os.path.join(example_folder, x) for x in example_fns if x.endswith('.png')] | |
| # Compose demo layout & data flow. | |
| with gr.Blocks(title=_TITLE, css="hf_demo/style.css") as demo: | |
| with gr.Row(): | |
| with gr.Column(scale=1): | |
| gr.Markdown('# ' + _TITLE) | |
| # with gr.Column(scale=0): | |
| # gr.DuplicateButton(value='Duplicate Space for private use', elem_id='duplicate-button') | |
| gr.Markdown(_DESCRIPTION) | |
| with gr.Row(variant='panel'): | |
| with gr.Column(scale=1): | |
| image_block = gr.Image(type='pil', image_mode='RGBA', height=256, label='Input image', tool=None, interactive=True) | |
| guide_text = gr.Markdown(_USER_GUIDE0, visible=True) | |
| gr.Examples( | |
| examples=examples_full, # NOTE: elements must match inputs list! | |
| inputs=[image_block], | |
| outputs=[image_block], | |
| cache_examples=False, | |
| label='Examples (click one of the images below to start)', | |
| examples_per_page=40 | |
| ) | |
| with gr.Column(scale=1): | |
| sam_block = gr.Image(type='pil', image_mode='RGBA', label="SAM output", height=256, interactive=False) | |
| crop_size_slider = gr.Slider(120, 240, 200, step=10, label='Crop size', interactive=True) | |
| with gr.Column(scale=1): | |
| input_block = gr.Image(type='pil', image_mode='RGB', label="Input to SyncDreamer", height=256, interactive=False) | |
| elevation_slider = gr.Slider(-10, 40, 30, step=5, label='Elevation angle', interactive=True) | |
| run_btn = gr.Button('Run Generation', variant='primary', interactive=False) | |
| update_guide = lambda GUIDE_TEXT: gr.update(value=GUIDE_TEXT) | |
| image_block.change(fn=partial(mask_prediction, mask_predictor), inputs=[image_block], outputs=[sam_block], queue=False)\ | |
| .success(fn=partial(update_guide, _USER_GUIDE1), outputs=[guide_text], queue=False) | |
| crop_size_slider.change(fn=resize_inputs, inputs=[sam_block, crop_size_slider], outputs=[input_block], queue=False)\ | |
| .success(fn=partial(update_guide, _USER_GUIDE2), outputs=[guide_text], queue=False) | |
| run_btn.click | |
| demo.queue().launch(share=False, max_threads=80) # auth=("admin", os.environ['PASSWD']) | |
| if __name__=="__main__": | |
| fire.Fire(run_demo) |