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import os |
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import os.path as osp |
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from argparse import ArgumentParser |
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from functools import partial |
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from pathlib import Path |
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import time |
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|
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import gradio as gr |
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import numpy as np |
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import torch |
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from PIL import Image |
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|
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import dnnlib |
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from gradio_utils import (ImageMask, draw_mask_on_image, draw_points_on_image, |
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get_latest_points_pair, get_valid_mask, |
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on_change_single_global_state) |
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from viz.renderer import Renderer, add_watermark_np |
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from huggingface_hub import snapshot_download |
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|
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model_dir = Path('./checkpoints') |
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snapshot_download('DragGan/DragGan-Models', |
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repo_type='model', local_dir=model_dir) |
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|
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parser = ArgumentParser() |
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parser.add_argument('--share', action='store_true') |
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parser.add_argument('--cache-dir', type=str, default='./checkpoints') |
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args = parser.parse_args() |
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cache_dir = args.cache_dir |
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device = 'cuda' |
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IS_SPACE = "DragGan/DragGan" in os.environ.get('SPACE_ID', '') |
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TIMEOUT = 80 |
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def reverse_point_pairs(points): |
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new_points = [] |
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for p in points: |
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new_points.append([p[1], p[0]]) |
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return new_points |
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def clear_state(global_state, target=None): |
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"""Clear target history state from global_state |
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If target is not defined, points and mask will be both removed. |
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1. set global_state['points'] as empty dict |
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2. set global_state['mask'] as full-one mask. |
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""" |
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if target is None: |
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target = ['point', 'mask'] |
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if not isinstance(target, list): |
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target = [target] |
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if 'point' in target: |
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global_state['points'] = dict() |
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print('Clear Points State!') |
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if 'mask' in target: |
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image_raw = global_state["images"]["image_raw"] |
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global_state['mask'] = np.ones((image_raw.size[1], image_raw.size[0]), |
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dtype=np.uint8) |
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print('Clear mask State!') |
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return global_state |
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def init_images(global_state): |
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"""This function is called only ones with Gradio App is started. |
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0. pre-process global_state, unpack value from global_state of need |
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1. Re-init renderer |
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2. run `renderer._render_drag_impl` with `is_drag=False` to generate |
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new image |
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3. Assign images to global state and re-generate mask |
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""" |
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|
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if isinstance(global_state, gr.State): |
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state = global_state.value |
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else: |
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state = global_state |
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|
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state['renderer'].init_network( |
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state['generator_params'], |
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valid_checkpoints_dict[state['pretrained_weight']], |
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state['params']['seed'], |
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None, |
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state['params']['latent_space'] == 'w+', |
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'const', |
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state['params']['trunc_psi'], |
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state['params']['trunc_cutoff'], |
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None, |
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state['params']['lr'] |
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) |
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state['renderer']._render_drag_impl(state['generator_params'], |
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is_drag=False, |
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to_pil=True) |
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|
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init_image = state['generator_params'].image |
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state['images']['image_orig'] = init_image |
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state['images']['image_raw'] = init_image |
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state['images']['image_show'] = Image.fromarray( |
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add_watermark_np(np.array(init_image))) |
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state['mask'] = np.ones((init_image.size[1], init_image.size[0]), |
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dtype=np.uint8) |
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return global_state |
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def update_image_draw(image, points, mask, show_mask, global_state=None): |
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|
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image_draw = draw_points_on_image(image, points) |
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if show_mask and mask is not None and not (mask == 0).all() and not ( |
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mask == 1).all(): |
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image_draw = draw_mask_on_image(image_draw, mask) |
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|
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image_draw = Image.fromarray(add_watermark_np(np.array(image_draw))) |
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if global_state is not None: |
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global_state['images']['image_show'] = image_draw |
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return image_draw |
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|
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def preprocess_mask_info(global_state, image): |
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"""Function to handle mask information. |
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1. last_mask is None: Do not need to change mask, return mask |
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2. last_mask is not None: |
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2.1 global_state is remove_mask: |
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2.2 global_state is add_mask: |
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""" |
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if isinstance(image, dict): |
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last_mask = get_valid_mask(image['mask']) |
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else: |
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last_mask = None |
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mask = global_state['mask'] |
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if (mask == 1).all(): |
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mask = last_mask |
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editing_mode = global_state['editing_state'] |
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|
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if last_mask is None: |
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return global_state |
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|
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if editing_mode == 'remove_mask': |
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updated_mask = np.clip(mask - last_mask, 0, 1) |
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print(f'Last editing_state is {editing_mode}, do remove.') |
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elif editing_mode == 'add_mask': |
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updated_mask = np.clip(mask + last_mask, 0, 1) |
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print(f'Last editing_state is {editing_mode}, do add.') |
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else: |
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updated_mask = mask |
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print(f'Last editing_state is {editing_mode}, ' |
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'do nothing to mask.') |
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global_state['mask'] = updated_mask |
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return global_state |
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allowed_checkpoints = [] |
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if IS_SPACE: |
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allowed_checkpoints = ["stylegan_human_v2_512.pkl", |
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"stylegan2_dogs_1024_pytorch.pkl"] |
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|
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valid_checkpoints_dict = { |
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f.name.split('.')[0]: str(f) |
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for f in Path(cache_dir).glob('*.pkl') |
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if f.name in allowed_checkpoints or not IS_SPACE |
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} |
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print('Valid checkpoint file:') |
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print(valid_checkpoints_dict) |
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|
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init_pkl = 'stylegan_human_v2_512' |
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|
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with gr.Blocks() as app: |
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gr.Markdown(""" |
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# DragGAN - Drag Your GAN |
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## Interactive Point-based Manipulation on the Generative Image Manifold |
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### Unofficial Gradio Demo |
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|
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**Due to high demand, only one model can be run at a time, or you can duplicate the space and run your own copy.** |
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|
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<a href="https://huggingface.co/spaces/radames/DragGan?duplicate=true" style="display: inline-block;margin-top: .5em;margin-right: .25em;" target="_blank"> |
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<img style="margin-bottom: 0em;display: inline;margin-top: -.25em;" src="https://bit.ly/3gLdBN6" alt="Duplicate Space"></a> for no queue on your own hardware.</p> |
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|
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* Official Repo: [XingangPan](https://github.com/XingangPan/DragGAN) |
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* Gradio Demo by: [LeoXing1996](https://github.com/LeoXing1996) © [OpenMMLab MMagic](https://github.com/open-mmlab/mmagic) |
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""") |
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global_state = gr.State({ |
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"images": { |
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}, |
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"temporal_params": { |
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}, |
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'mask': |
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None, |
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'last_mask': None, |
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'show_mask': True, |
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"generator_params": dnnlib.EasyDict(), |
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"params": { |
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"seed": 0, |
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"motion_lambda": 20, |
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"r1_in_pixels": 3, |
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"r2_in_pixels": 12, |
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"magnitude_direction_in_pixels": 1.0, |
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"latent_space": "w+", |
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"trunc_psi": 0.7, |
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"trunc_cutoff": None, |
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"lr": 0.001, |
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}, |
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"device": device, |
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"draw_interval": 1, |
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"renderer": Renderer(disable_timing=True), |
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"points": {}, |
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"curr_point": None, |
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"curr_type_point": "start", |
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'editing_state': 'add_points', |
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'pretrained_weight': init_pkl |
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}) |
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global_state = init_images(global_state) |
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with gr.Row(): |
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|
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with gr.Row(): |
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|
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with gr.Column(scale=3): |
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with gr.Row(): |
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|
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with gr.Column(scale=1, min_width=10): |
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gr.Markdown(value='Pickle', show_label=False) |
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|
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with gr.Column(scale=4, min_width=10): |
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form_pretrained_dropdown = gr.Dropdown( |
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choices=list(valid_checkpoints_dict.keys()), |
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label="Pretrained Model", |
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value=init_pkl, |
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) |
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with gr.Row(): |
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with gr.Column(scale=1, min_width=10): |
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gr.Markdown(value='Latent', show_label=False) |
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|
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with gr.Column(scale=4, min_width=10): |
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form_seed_number = gr.Slider( |
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mininium=0, |
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maximum=2**32-1, |
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step=1, |
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value=global_state.value['params']['seed'], |
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interactive=True, |
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randomize=True, |
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label="Seed", |
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) |
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form_lr_number = gr.Number( |
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value=global_state.value["params"]["lr"], |
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interactive=True, |
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label="Step Size") |
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|
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with gr.Row(): |
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with gr.Column(scale=2, min_width=10): |
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form_reset_image = gr.Button("Reset Image") |
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with gr.Column(scale=3, min_width=10): |
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form_latent_space = gr.Radio( |
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['w', 'w+'], |
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value=global_state.value['params'] |
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['latent_space'], |
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interactive=True, |
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label='Latent space to optimize', |
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show_label=False, |
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) |
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|
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with gr.Row(): |
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with gr.Column(scale=1, min_width=10): |
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gr.Markdown(value='Drag', show_label=False) |
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with gr.Column(scale=4, min_width=10): |
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with gr.Row(): |
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with gr.Column(scale=1, min_width=10): |
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enable_add_points = gr.Button('Add Points') |
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with gr.Column(scale=1, min_width=10): |
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undo_points = gr.Button('Reset Points') |
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with gr.Row(): |
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with gr.Column(scale=1, min_width=10): |
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form_start_btn = gr.Button("Start") |
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with gr.Column(scale=1, min_width=10): |
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form_stop_btn = gr.Button("Stop") |
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|
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form_steps_number = gr.Number(value=0, |
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label="Steps", |
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interactive=False) |
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|
|
|
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with gr.Row(): |
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with gr.Column(scale=1, min_width=10): |
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gr.Markdown(value='Mask', show_label=False) |
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with gr.Column(scale=4, min_width=10): |
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enable_add_mask = gr.Button('Edit Flexible Area') |
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with gr.Row(): |
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with gr.Column(scale=1, min_width=10): |
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form_reset_mask_btn = gr.Button("Reset mask") |
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with gr.Column(scale=1, min_width=10): |
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show_mask = gr.Checkbox( |
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label='Show Mask', |
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value=global_state.value['show_mask'], |
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show_label=False) |
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|
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with gr.Row(): |
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form_lambda_number = gr.Number( |
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value=global_state.value["params"] |
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["motion_lambda"], |
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interactive=True, |
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label="Lambda", |
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) |
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|
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form_draw_interval_number = gr.Number( |
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value=global_state.value["draw_interval"], |
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label="Draw Interval (steps)", |
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interactive=True, |
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visible=False) |
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|
|
|
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with gr.Column(scale=8): |
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form_image = ImageMask( |
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|
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brush_radius=20).style( |
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width=768, |
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height=768) |
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gr.Markdown(""" |
|
## Quick Start |
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|
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1. Select desired `Pretrained Model` and adjust `Seed` to generate an |
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initial image. |
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2. Click on image to add control points. |
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3. Click `Start` and enjoy it! |
|
|
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## Advance Usage |
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|
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1. Change `Step Size` to adjust learning rate in drag optimization. |
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2. Select `w` or `w+` to change latent space to optimize: |
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* Optimize on `w` space may cause greater influence to the image. |
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* Optimize on `w+` space may work slower than `w`, but usually achieve |
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better results. |
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* Note that changing the latent space will reset the image, points and |
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mask (this has the same effect as `Reset Image` button). |
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3. Click `Edit Flexible Area` to create a mask and constrain the |
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unmasked region to remain unchanged. |
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|
|
|
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""") |
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gr.HTML(""" |
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<style> |
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.container { |
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position: absolute; |
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height: 50px; |
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text-align: center; |
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line-height: 50px; |
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width: 100%; |
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} |
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</style> |
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<div class="container"> |
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Gradio demo supported by |
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<img src="https://avatars.githubusercontent.com/u/10245193?s=200&v=4" height="20" width="20" style="display:inline;"> |
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<a href="https://github.com/open-mmlab/mmagic">OpenMMLab MMagic</a> |
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</div> |
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""") |
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|
|
|
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def on_change_pretrained_dropdown(pretrained_value, global_state): |
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"""Function to handle model change. |
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1. Set pretrained value to global_state |
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2. Re-init images and clear all states |
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""" |
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|
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global_state['pretrained_weight'] = pretrained_value |
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init_images(global_state) |
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clear_state(global_state) |
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|
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return global_state, global_state["images"]['image_show'] |
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|
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form_pretrained_dropdown.change( |
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on_change_pretrained_dropdown, |
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inputs=[form_pretrained_dropdown, global_state], |
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outputs=[global_state, form_image], |
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queue=True, |
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) |
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|
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def on_click_reset_image(global_state): |
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"""Reset image to the original one and clear all states |
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1. Re-init images |
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2. Clear all states |
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""" |
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|
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init_images(global_state) |
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clear_state(global_state) |
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|
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return global_state, global_state['images']['image_show'] |
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|
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form_reset_image.click( |
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on_click_reset_image, |
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inputs=[global_state], |
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outputs=[global_state, form_image], |
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queue=False, |
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) |
|
|
|
|
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def on_change_update_image_seed(seed, global_state): |
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"""Function to handle generation seed change. |
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1. Set seed to global_state |
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2. Re-init images and clear all states |
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""" |
|
|
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global_state["params"]["seed"] = int(seed) |
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init_images(global_state) |
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clear_state(global_state) |
|
|
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return global_state, global_state['images']['image_show'] |
|
|
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form_seed_number.change( |
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on_change_update_image_seed, |
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inputs=[form_seed_number, global_state], |
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outputs=[global_state, form_image], |
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) |
|
|
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def on_click_latent_space(latent_space, global_state): |
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"""Function to reset latent space to optimize. |
|
NOTE: this function we reset the image and all controls |
|
1. Set latent-space to global_state |
|
2. Re-init images and clear all state |
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""" |
|
|
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global_state['params']['latent_space'] = latent_space |
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init_images(global_state) |
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clear_state(global_state) |
|
|
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return global_state, global_state['images']['image_show'] |
|
|
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form_latent_space.change(on_click_latent_space, |
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inputs=[form_latent_space, global_state], |
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outputs=[global_state, form_image]) |
|
|
|
|
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form_lambda_number.change( |
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partial(on_change_single_global_state, ["params", "motion_lambda"]), |
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inputs=[form_lambda_number, global_state], |
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outputs=[global_state], |
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) |
|
|
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def on_change_lr(lr, global_state): |
|
if lr == 0: |
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print('lr is 0, do nothing.') |
|
return global_state |
|
else: |
|
global_state["params"]["lr"] = lr |
|
renderer = global_state['renderer'] |
|
renderer.update_lr(lr) |
|
print('New optimizer: ') |
|
print(renderer.w_optim) |
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return global_state |
|
|
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form_lr_number.change( |
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on_change_lr, |
|
inputs=[form_lr_number, global_state], |
|
outputs=[global_state], |
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queue=False, |
|
) |
|
|
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def on_click_start(global_state, image): |
|
p_in_pixels = [] |
|
t_in_pixels = [] |
|
valid_points = [] |
|
|
|
|
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global_state = preprocess_mask_info(global_state, image) |
|
|
|
|
|
if len(global_state["points"]) == 0: |
|
|
|
image_raw = global_state['images']['image_raw'] |
|
update_image_draw( |
|
image_raw, |
|
global_state['points'], |
|
global_state['mask'], |
|
global_state['show_mask'], |
|
global_state, |
|
) |
|
|
|
yield ( |
|
global_state, |
|
0, |
|
global_state['images']['image_show'], |
|
|
|
gr.Button.update(interactive=True), |
|
gr.Button.update(interactive=True), |
|
gr.Button.update(interactive=True), |
|
gr.Button.update(interactive=True), |
|
gr.Button.update(interactive=True), |
|
|
|
gr.Radio.update(interactive=True), |
|
gr.Button.update(interactive=True), |
|
|
|
gr.Button.update(interactive=False), |
|
|
|
|
|
gr.Dropdown.update(interactive=True), |
|
gr.Number.update(interactive=True), |
|
gr.Number.update(interactive=True), |
|
gr.Button.update(interactive=True), |
|
gr.Button.update(interactive=True), |
|
gr.Checkbox.update(interactive=True), |
|
|
|
gr.Number.update(interactive=True), |
|
) |
|
else: |
|
|
|
|
|
for key_point, point in global_state["points"].items(): |
|
try: |
|
p_start = point.get("start_temp", point["start"]) |
|
p_end = point["target"] |
|
|
|
if p_start is None or p_end is None: |
|
continue |
|
|
|
except KeyError: |
|
continue |
|
|
|
p_in_pixels.append(p_start) |
|
t_in_pixels.append(p_end) |
|
valid_points.append(key_point) |
|
|
|
mask = torch.tensor(global_state['mask']).float() |
|
drag_mask = 1 - mask |
|
|
|
renderer: Renderer = global_state["renderer"] |
|
global_state['temporal_params']['stop'] = False |
|
global_state['editing_state'] = 'running' |
|
|
|
|
|
p_to_opt = reverse_point_pairs(p_in_pixels) |
|
t_to_opt = reverse_point_pairs(t_in_pixels) |
|
print('Running with:') |
|
print(f' Source: {p_in_pixels}') |
|
print(f' Target: {t_in_pixels}') |
|
step_idx = 0 |
|
last_time = time.time() |
|
while True: |
|
|
|
print(f'Running time: {time.time() - last_time}') |
|
if IS_SPACE and time.time() - last_time > TIMEOUT: |
|
print('Timeout break!') |
|
break |
|
if global_state["temporal_params"]["stop"] or global_state['generator_params']["stop"]: |
|
break |
|
|
|
|
|
renderer._render_drag_impl( |
|
global_state['generator_params'], |
|
p_to_opt, |
|
t_to_opt, |
|
drag_mask, |
|
global_state['params']['motion_lambda'], |
|
reg=0, |
|
feature_idx=5, |
|
r1=global_state['params']['r1_in_pixels'], |
|
r2=global_state['params']['r2_in_pixels'], |
|
|
|
|
|
trunc_psi=global_state['params']['trunc_psi'], |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
is_drag=True, |
|
to_pil=True) |
|
|
|
if step_idx % global_state['draw_interval'] == 0: |
|
print('Current Source:') |
|
for key_point, p_i, t_i in zip(valid_points, p_to_opt, |
|
t_to_opt): |
|
global_state["points"][key_point]["start_temp"] = [ |
|
p_i[1], |
|
p_i[0], |
|
] |
|
global_state["points"][key_point]["target"] = [ |
|
t_i[1], |
|
t_i[0], |
|
] |
|
start_temp = global_state["points"][key_point][ |
|
"start_temp"] |
|
print(f' {start_temp}') |
|
|
|
image_result = global_state['generator_params']['image'] |
|
image_draw = update_image_draw( |
|
image_result, |
|
global_state['points'], |
|
global_state['mask'], |
|
global_state['show_mask'], |
|
global_state, |
|
) |
|
global_state['images']['image_raw'] = image_result |
|
|
|
yield ( |
|
global_state, |
|
step_idx, |
|
global_state['images']['image_show'], |
|
|
|
gr.Button.update(interactive=False), |
|
gr.Button.update(interactive=False), |
|
gr.Button.update(interactive=False), |
|
gr.Button.update(interactive=False), |
|
gr.Button.update(interactive=False), |
|
|
|
gr.Radio.update(interactive=False), |
|
gr.Button.update(interactive=False), |
|
|
|
gr.Button.update(interactive=True), |
|
|
|
|
|
gr.Dropdown.update(interactive=False), |
|
gr.Number.update(interactive=False), |
|
gr.Number.update(interactive=False), |
|
gr.Button.update(interactive=False), |
|
gr.Button.update(interactive=False), |
|
gr.Checkbox.update(interactive=False), |
|
|
|
gr.Number.update(interactive=False), |
|
) |
|
|
|
|
|
step_idx += 1 |
|
|
|
image_result = global_state['generator_params']['image'] |
|
global_state['images']['image_raw'] = image_result |
|
image_draw = update_image_draw(image_result, |
|
global_state['points'], |
|
global_state['mask'], |
|
global_state['show_mask'], |
|
global_state) |
|
|
|
|
|
|
|
|
|
global_state['editing_state'] = 'add_points' |
|
|
|
yield ( |
|
global_state, |
|
0, |
|
global_state['images']['image_show'], |
|
|
|
gr.Button.update(interactive=True), |
|
gr.Button.update(interactive=True), |
|
gr.Button.update(interactive=True), |
|
gr.Button.update(interactive=True), |
|
gr.Button.update(interactive=True), |
|
|
|
gr.Radio.update(interactive=True), |
|
gr.Button.update(interactive=True), |
|
|
|
gr.Button.update(interactive=False), |
|
|
|
|
|
gr.Dropdown.update(interactive=True), |
|
gr.Number.update(interactive=True), |
|
gr.Number.update(interactive=True), |
|
gr.Checkbox.update(interactive=True), |
|
gr.Number.update(interactive=True), |
|
) |
|
|
|
form_start_btn.click( |
|
on_click_start, |
|
inputs=[global_state, form_image], |
|
outputs=[ |
|
global_state, |
|
form_steps_number, |
|
form_image, |
|
|
|
|
|
form_reset_image, |
|
enable_add_points, |
|
enable_add_mask, |
|
undo_points, |
|
form_reset_mask_btn, |
|
form_latent_space, |
|
form_start_btn, |
|
form_stop_btn, |
|
|
|
|
|
form_pretrained_dropdown, |
|
form_seed_number, |
|
form_lr_number, |
|
show_mask, |
|
form_lambda_number, |
|
], |
|
) |
|
|
|
def on_click_stop(global_state): |
|
"""Function to handle stop button is clicked. |
|
1. send a stop signal by set global_state["temporal_params"]["stop"] as True |
|
2. Disable Stop button |
|
""" |
|
global_state["temporal_params"]["stop"] = True |
|
|
|
return global_state, gr.Button.update(interactive=False) |
|
|
|
form_stop_btn.click(on_click_stop, |
|
inputs=[global_state], |
|
outputs=[global_state, form_stop_btn], |
|
queue=False) |
|
|
|
form_draw_interval_number.change( |
|
partial( |
|
on_change_single_global_state, |
|
"draw_interval", |
|
map_transform=lambda x: int(x), |
|
), |
|
inputs=[form_draw_interval_number, global_state], |
|
outputs=[global_state], |
|
queue=False, |
|
) |
|
|
|
def on_click_remove_point(global_state): |
|
choice = global_state["curr_point"] |
|
del global_state["points"][choice] |
|
|
|
choices = list(global_state["points"].keys()) |
|
|
|
if len(choices) > 0: |
|
global_state["curr_point"] = choices[0] |
|
|
|
return ( |
|
gr.Dropdown.update(choices=choices, value=choices[0]), |
|
global_state, |
|
) |
|
|
|
|
|
def on_click_reset_mask(global_state): |
|
global_state['mask'] = np.ones( |
|
( |
|
global_state["images"]["image_raw"].size[1], |
|
global_state["images"]["image_raw"].size[0], |
|
), |
|
dtype=np.uint8, |
|
) |
|
image_draw = update_image_draw(global_state['images']['image_raw'], |
|
global_state['points'], |
|
global_state['mask'], |
|
global_state['show_mask'], global_state) |
|
return global_state, image_draw |
|
|
|
form_reset_mask_btn.click( |
|
on_click_reset_mask, |
|
inputs=[global_state], |
|
outputs=[global_state, form_image], |
|
) |
|
|
|
|
|
def on_click_enable_draw(global_state, image): |
|
"""Function to start add mask mode. |
|
1. Preprocess mask info from last state |
|
2. Change editing state to add_mask |
|
3. Set curr image with points and mask |
|
""" |
|
global_state = preprocess_mask_info(global_state, image) |
|
global_state['editing_state'] = 'add_mask' |
|
image_raw = global_state['images']['image_raw'] |
|
image_draw = update_image_draw(image_raw, global_state['points'], |
|
global_state['mask'], True, |
|
global_state) |
|
return (global_state, |
|
gr.Image.update(value=image_draw, interactive=True)) |
|
|
|
def on_click_remove_draw(global_state, image): |
|
"""Function to start remove mask mode. |
|
1. Preprocess mask info from last state |
|
2. Change editing state to remove_mask |
|
3. Set curr image with points and mask |
|
""" |
|
global_state = preprocess_mask_info(global_state, image) |
|
global_state['edinting_state'] = 'remove_mask' |
|
image_raw = global_state['images']['image_raw'] |
|
image_draw = update_image_draw(image_raw, global_state['points'], |
|
global_state['mask'], True, |
|
global_state) |
|
return (global_state, |
|
gr.Image.update(value=image_draw, interactive=True)) |
|
|
|
enable_add_mask.click(on_click_enable_draw, |
|
inputs=[global_state, form_image], |
|
outputs=[ |
|
global_state, |
|
form_image, |
|
], |
|
queue=False) |
|
|
|
def on_click_add_point(global_state, image: dict): |
|
"""Function switch from add mask mode to add points mode. |
|
1. Updaste mask buffer if need |
|
2. Change global_state['editing_state'] to 'add_points' |
|
3. Set current image with mask |
|
""" |
|
|
|
global_state = preprocess_mask_info(global_state, image) |
|
global_state['editing_state'] = 'add_points' |
|
mask = global_state['mask'] |
|
image_raw = global_state['images']['image_raw'] |
|
image_draw = update_image_draw(image_raw, global_state['points'], mask, |
|
global_state['show_mask'], global_state) |
|
|
|
return (global_state, |
|
gr.Image.update(value=image_draw, interactive=False)) |
|
|
|
enable_add_points.click(on_click_add_point, |
|
inputs=[global_state, form_image], |
|
outputs=[global_state, form_image], |
|
queue=False) |
|
|
|
def on_click_image(global_state, evt: gr.SelectData): |
|
"""This function only support click for point selection |
|
""" |
|
xy = evt.index |
|
if global_state['editing_state'] != 'add_points': |
|
print(f'In {global_state["editing_state"]} state. ' |
|
'Do not add points.') |
|
|
|
return global_state, global_state['images']['image_show'] |
|
|
|
points = global_state["points"] |
|
|
|
point_idx = get_latest_points_pair(points) |
|
if point_idx is None: |
|
points[0] = {'start': xy, 'target': None} |
|
print(f'Click Image - Start - {xy}') |
|
elif points[point_idx].get('target', None) is None: |
|
points[point_idx]['target'] = xy |
|
print(f'Click Image - Target - {xy}') |
|
else: |
|
points[point_idx + 1] = {'start': xy, 'target': None} |
|
print(f'Click Image - Start - {xy}') |
|
|
|
image_raw = global_state['images']['image_raw'] |
|
image_draw = update_image_draw( |
|
image_raw, |
|
global_state['points'], |
|
global_state['mask'], |
|
global_state['show_mask'], |
|
global_state, |
|
) |
|
|
|
return global_state, image_draw |
|
|
|
form_image.select( |
|
on_click_image, |
|
inputs=[global_state], |
|
outputs=[global_state, form_image], |
|
queue=False, |
|
) |
|
|
|
def on_click_clear_points(global_state): |
|
"""Function to handle clear all control points |
|
1. clear global_state['points'] (clear_state) |
|
2. re-init network |
|
2. re-draw image |
|
""" |
|
clear_state(global_state, target='point') |
|
|
|
renderer: Renderer = global_state["renderer"] |
|
renderer.feat_refs = None |
|
|
|
image_raw = global_state['images']['image_raw'] |
|
image_draw = update_image_draw(image_raw, {}, global_state['mask'], |
|
global_state['show_mask'], global_state) |
|
return global_state, image_draw |
|
|
|
undo_points.click(on_click_clear_points, |
|
inputs=[global_state], |
|
outputs=[global_state, form_image], |
|
queue=False) |
|
|
|
def on_click_show_mask(global_state, show_mask): |
|
"""Function to control whether show mask on image.""" |
|
global_state['show_mask'] = show_mask |
|
|
|
image_raw = global_state['images']['image_raw'] |
|
image_draw = update_image_draw( |
|
image_raw, |
|
global_state['points'], |
|
global_state['mask'], |
|
global_state['show_mask'], |
|
global_state, |
|
) |
|
return global_state, image_draw |
|
|
|
show_mask.change( |
|
on_click_show_mask, |
|
inputs=[global_state, show_mask], |
|
outputs=[global_state, form_image], |
|
queue=False, |
|
) |
|
|
|
print("SHAReD: Start app", parser.parse_args()) |
|
gr.close_all() |
|
app.queue(concurrency_count=2, max_size=200, api_open=False) |
|
app.launch(share=args.share, show_api=False) |
|
|