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| from main import run_app, run_train, run_inference, run_generate_frame, run_interpolate_frames, resize_images | |
| from evaluate import run_evaluate, get_score | |
| import spaces | |
| from PIL import Image | |
| import cv2 | |
| import os | |
| import gradio as gr | |
| with gr.Blocks() as demo: | |
| with gr.Row(): | |
| with gr.Column(): | |
| char_imgs = gr.Gallery(type="pil", label="Images of the Character") | |
| mocap = gr.Video(label="Motion-Capture Video") | |
| frame_imgs = gr.Gallery(type="pil", label="Reference Images of Each Frame") | |
| poses = gr.JSON(label="Pose Coordinates") | |
| tr_steps = gr.Number(label="Training steps", value=10) | |
| inf_steps = gr.Number(label="Inference steps", value=10) | |
| fps = gr.Number(label="Output frame rate", value=12) | |
| modelId = gr.Text(label="Model Id", value="fine_tuned_pcdms") | |
| remove_bg = gr.Checkbox(label="Remove background", value=False) | |
| resize_inputs = gr.Checkbox(label="Resize images to match video", value=True) | |
| img_width = gr.Number(label="Output width", value=1920) | |
| img_height = gr.Number(label="Output height", value=1080) | |
| interp_frame1 = gr.Image(type="pil", label="Interpolation Start Frame") | |
| interp_frame2 = gr.Image(type="pil", label="Interpolation End Frame") | |
| times_to_interp = gr.Number(label="Times to Interpolate", value=1) | |
| name = gr.Text(label="Name", value="") | |
| train_btn = gr.Button(value="Train") | |
| inference_btn = gr.Button(value="Inference") | |
| generate_frame_btn = gr.Button(value="Generate Frame") | |
| submit_btn = gr.Button(value="Generate") | |
| interp_btn = gr.Button(value="Interpolate Frames") | |
| eval_btn = gr.Button(value="Evaluate All") | |
| eval_btn2 = gr.Button(value="Evaluate") | |
| resize_btn = gr.Button(value="Resize") | |
| with gr.Column(): | |
| animation = gr.Video(label="Result") | |
| frames = gr.Gallery(type="pil", label="Frames", format="png") | |
| frames_thumb = gr.Gallery(type="pil", label="Thumbnails", format="png") | |
| pose_coords = gr.JSON(label="Pose Coordinates") | |
| reference = gr.Gallery(type="pil", label="Reference Images", format="png") | |
| eval_scores = gr.JSON(label="Evaluation Scores") | |
| submit_btn.click( | |
| run_app, inputs=[char_imgs, mocap, tr_steps, inf_steps, fps, remove_bg, resize_inputs], outputs=[animation, frames] | |
| ) | |
| train_btn.click( | |
| run_train, inputs=[char_imgs, tr_steps, modelId, remove_bg, resize_inputs], outputs=[] | |
| ) | |
| inference_btn.click( | |
| run_inference, inputs=[char_imgs, mocap, frame_imgs, tr_steps, inf_steps, fps, modelId, img_width, img_height, remove_bg, resize_inputs], outputs=[animation, frames, frames_thumb, pose_coords, reference] | |
| ) | |
| generate_frame_btn.click( | |
| run_generate_frame, inputs=[char_imgs, poses, tr_steps, inf_steps, modelId, img_width, img_height, remove_bg, resize_inputs], outputs=[frames, frames_thumb] | |
| ) | |
| interp_btn.click( | |
| run_interpolate_frames, inputs=[interp_frame1, interp_frame2, times_to_interp, remove_bg], outputs=[frames, frames_thumb] | |
| ) | |
| eval_btn.click( | |
| run_evaluate, inputs=[], outputs=[eval_scores] | |
| ) | |
| eval_btn2.click( | |
| get_score, inputs=[name, char_imgs, mocap, tr_steps, inf_steps, fps, remove_bg], outputs=[eval_scores] | |
| ) | |
| resize_btn.click( | |
| resize_images, inputs=[frame_imgs, img_width, img_height], outputs=[frames] | |
| ) | |
| demo.launch(share=True, show_error=True) | |