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Running
on
Zero
# coding: utf-8 | |
""" | |
Pipeline for gradio | |
""" | |
import gradio as gr | |
from .config.argument_config import ArgumentConfig | |
from .live_portrait_pipeline import LivePortraitPipeline | |
from .utils.io import load_img_online | |
from .utils.rprint import rlog as log | |
from .utils.crop import prepare_paste_back, paste_back | |
from .utils.camera import get_rotation_matrix | |
from .utils.retargeting_utils import calc_eye_close_ratio, calc_lip_close_ratio | |
def update_args(args, user_args): | |
"""update the args according to user inputs | |
""" | |
for k, v in user_args.items(): | |
if hasattr(args, k): | |
setattr(args, k, v) | |
return args | |
class GradioPipeline(LivePortraitPipeline): | |
def __init__(self, inference_cfg, crop_cfg, args: ArgumentConfig): | |
super().__init__(inference_cfg, crop_cfg) | |
# self.live_portrait_wrapper = self.live_portrait_wrapper | |
self.args = args | |
# for single image retargeting | |
self.start_prepare = False | |
self.f_s_user = None | |
self.x_c_s_info_user = None | |
self.x_s_user = None | |
self.source_lmk_user = None | |
self.mask_ori = None | |
self.img_rgb = None | |
self.crop_M_c2o = None | |
def execute_video( | |
self, | |
input_image_path, | |
input_video_path, | |
flag_relative_input, | |
flag_do_crop_input, | |
flag_remap_input, | |
): | |
""" for video driven potrait animation | |
""" | |
if input_image_path is not None and input_video_path is not None: | |
args_user = { | |
'source_image': input_image_path, | |
'driving_info': input_video_path, | |
'flag_relative': flag_relative_input, | |
'flag_do_crop': flag_do_crop_input, | |
'flag_pasteback': flag_remap_input, | |
} | |
# update config from user input | |
self.args = update_args(self.args, args_user) | |
self.live_portrait_wrapper.update_config(self.args.__dict__) | |
self.cropper.update_config(self.args.__dict__) | |
# video driven animation | |
video_path, video_path_concat = self.execute(self.args) | |
gr.Info("Run successfully!", duration=2) | |
return video_path, video_path_concat, | |
else: | |
raise gr.Error("The input source portrait or driving video hasn't been prepared yet π₯!", duration=5) | |
def execute_image(self, input_eye_ratio: float, input_lip_ratio: float): | |
""" for single image retargeting | |
""" | |
if input_eye_ratio is None or input_eye_ratio is None: | |
raise gr.Error("Invalid ratio input π₯!", duration=5) | |
elif self.f_s_user is None: | |
if self.start_prepare: | |
raise gr.Error( | |
"The source portrait is under processing π₯! Please wait for a second.", | |
duration=5 | |
) | |
else: | |
raise gr.Error( | |
"The source portrait hasn't been prepared yet π₯! Please scroll to the top of the page to upload.", | |
duration=5 | |
) | |
else: | |
# β_eyes,i = R_eyes(x_s; c_s,eyes, c_d,eyes,i) | |
combined_eye_ratio_tensor = self.live_portrait_wrapper.calc_combined_eye_ratio([[input_eye_ratio]], self.source_lmk_user) | |
eyes_delta = self.live_portrait_wrapper.retarget_eye(self.x_s_user, combined_eye_ratio_tensor) | |
# β_lip,i = R_lip(x_s; c_s,lip, c_d,lip,i) | |
combined_lip_ratio_tensor = self.live_portrait_wrapper.calc_combined_lip_ratio([[input_lip_ratio]], self.source_lmk_user) | |
lip_delta = self.live_portrait_wrapper.retarget_lip(self.x_s_user, combined_lip_ratio_tensor) | |
num_kp = self.x_s_user.shape[1] | |
# default: use x_s | |
x_d_new = self.x_s_user + eyes_delta.reshape(-1, num_kp, 3) + lip_delta.reshape(-1, num_kp, 3) | |
# D(W(f_s; x_s, xβ²_d)) | |
out = self.live_portrait_wrapper.warp_decode(self.f_s_user, self.x_s_user, x_d_new) | |
out = self.live_portrait_wrapper.parse_output(out['out'])[0] | |
out_to_ori_blend = paste_back(out, self.crop_M_c2o, self.img_rgb, self.mask_ori) | |
gr.Info("Run successfully!", duration=2) | |
return out, out_to_ori_blend | |
def prepare_retargeting(self, input_image_path, flag_do_crop = True): | |
""" for single image retargeting | |
""" | |
if input_image_path is not None: | |
gr.Info("Upload successfully!", duration=2) | |
self.start_prepare = True | |
inference_cfg = self.live_portrait_wrapper.cfg | |
######## process source portrait ######## | |
img_rgb = load_img_online(input_image_path, mode='rgb', max_dim=1280, n=16) | |
log(f"Load source image from {input_image_path}.") | |
crop_info = self.cropper.crop_single_image(img_rgb) | |
if flag_do_crop: | |
I_s = self.live_portrait_wrapper.prepare_source(crop_info['img_crop_256x256']) | |
else: | |
I_s = self.live_portrait_wrapper.prepare_source(img_rgb) | |
x_s_info = self.live_portrait_wrapper.get_kp_info(I_s) | |
R_s = get_rotation_matrix(x_s_info['pitch'], x_s_info['yaw'], x_s_info['roll']) | |
############################################ | |
# record global info for next time use | |
self.f_s_user = self.live_portrait_wrapper.extract_feature_3d(I_s) | |
self.x_s_user = self.live_portrait_wrapper.transform_keypoint(x_s_info) | |
self.x_s_info_user = x_s_info | |
self.source_lmk_user = crop_info['lmk_crop'] | |
self.img_rgb = img_rgb | |
self.crop_M_c2o = crop_info['M_c2o'] | |
self.mask_ori = prepare_paste_back(inference_cfg.mask_crop, crop_info['M_c2o'], dsize=(img_rgb.shape[1], img_rgb.shape[0])) | |
# update slider | |
eye_close_ratio = calc_eye_close_ratio(self.source_lmk_user[None]) | |
eye_close_ratio = float(eye_close_ratio.squeeze(0).mean()) | |
lip_close_ratio = calc_lip_close_ratio(self.source_lmk_user[None]) | |
lip_close_ratio = float(lip_close_ratio.squeeze(0).mean()) | |
# for vis | |
self.I_s_vis = self.live_portrait_wrapper.parse_output(I_s)[0] | |
return eye_close_ratio, lip_close_ratio, self.I_s_vis | |
else: | |
# when press the clear button, go here | |
return 0.8, 0.8, self.I_s_vis | |