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Runtime error
chore: remove gr.Info
Browse files- app.py +1 -2
- src/gradio_pipeline.py +3 -3
app.py
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@@ -12,10 +12,9 @@ from src.gradio_pipeline import GradioPipeline
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from src.config.crop_config import CropConfig
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from src.config.argument_config import ArgumentConfig
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from src.config.inference_config import InferenceConfig
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import gdown
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import os
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import spaces
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# folder_url = f"https://drive.google.com/drive/folders/1UtKgzKjFAOmZkhNK-OYT0caJ_w2XAnib"
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# gdown.download_folder(url=folder_url, output="pretrained_weights", quiet=False)
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from src.config.crop_config import CropConfig
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from src.config.argument_config import ArgumentConfig
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from src.config.inference_config import InferenceConfig
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import spaces
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# import gdown
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# folder_url = f"https://drive.google.com/drive/folders/1UtKgzKjFAOmZkhNK-OYT0caJ_w2XAnib"
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# gdown.download_folder(url=folder_url, output="pretrained_weights", quiet=False)
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src/gradio_pipeline.py
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@@ -61,7 +61,7 @@ class GradioPipeline(LivePortraitPipeline):
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self.cropper.update_config(self.args.__dict__)
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# video driven animation
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video_path, video_path_concat = self.execute(self.args)
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gr.Info("Run successfully!", duration=2)
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return video_path, video_path_concat,
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else:
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raise gr.Error("The input source portrait or driving video hasn't been prepared yet 💥!", duration=5)
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@@ -96,7 +96,7 @@ class GradioPipeline(LivePortraitPipeline):
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out = self.live_portrait_wrapper.warp_decode(self.f_s_user, self.x_s_user, x_d_new)
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out = self.live_portrait_wrapper.parse_output(out['out'])[0]
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out_to_ori_blend = paste_back(out, self.crop_M_c2o, self.img_rgb, self.mask_ori)
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gr.Info("Run successfully!", duration=2)
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return out, out_to_ori_blend
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@@ -104,7 +104,7 @@ class GradioPipeline(LivePortraitPipeline):
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""" for single image retargeting
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"""
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if input_image_path is not None:
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gr.Info("Upload successfully!", duration=2)
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self.start_prepare = True
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inference_cfg = self.live_portrait_wrapper.cfg
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######## process source portrait ########
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self.cropper.update_config(self.args.__dict__)
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# video driven animation
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video_path, video_path_concat = self.execute(self.args)
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# gr.Info("Run successfully!", duration=2)
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return video_path, video_path_concat,
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else:
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raise gr.Error("The input source portrait or driving video hasn't been prepared yet 💥!", duration=5)
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out = self.live_portrait_wrapper.warp_decode(self.f_s_user, self.x_s_user, x_d_new)
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out = self.live_portrait_wrapper.parse_output(out['out'])[0]
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out_to_ori_blend = paste_back(out, self.crop_M_c2o, self.img_rgb, self.mask_ori)
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# gr.Info("Run successfully!", duration=2)
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return out, out_to_ori_blend
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""" for single image retargeting
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"""
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if input_image_path is not None:
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# gr.Info("Upload successfully!", duration=2)
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self.start_prepare = True
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inference_cfg = self.live_portrait_wrapper.cfg
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######## process source portrait ########
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