Spaces:
Running
on
Zero
Running
on
Zero
Commit
·
8dea111
1
Parent(s):
8553e9e
update
Browse files- app.py +3 -1
- requirements.txt +3 -3
app.py
CHANGED
@@ -26,6 +26,7 @@ import collections
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import numpy as np
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import gradio as gr
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from PIL import Image
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import torch
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from pathlib import Path
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@@ -131,6 +132,7 @@ def get_points(img, original_image, sel_pix, evt: gr.SelectData):
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return [img if isinstance(img, np.ndarray) else np.array(img), original_image]
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def gesturenet_inference(ref_image, prompt, selected_points):
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# Check some paramter, must have prompt and selected points
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@@ -178,7 +180,7 @@ def gesturenet_inference(ref_image, prompt, selected_points):
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project_config = ProjectConfiguration(project_dir=config["output_dir"], logging_dir=Path(config["output_dir"], config["logging_name"])),
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)
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print("device is ", accelerator.device)
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-
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feature_extractor = CLIPImageProcessor.from_pretrained(
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config["pretrained_model_name_or_path"], subfolder="feature_extractor", revision=None
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) # This instance has now weight, they are just seeting file
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import numpy as np
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import gradio as gr
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from PIL import Image
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+
import spaces
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import torch
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from pathlib import Path
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return [img if isinstance(img, np.ndarray) else np.array(img), original_image]
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+
@spaces.GPU(duration=120)
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def gesturenet_inference(ref_image, prompt, selected_points):
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# Check some paramter, must have prompt and selected points
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project_config = ProjectConfiguration(project_dir=config["output_dir"], logging_dir=Path(config["output_dir"], config["logging_name"])),
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)
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print("device is ", accelerator.device)
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+
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feature_extractor = CLIPImageProcessor.from_pretrained(
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config["pretrained_model_name_or_path"], subfolder="feature_extractor", revision=None
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) # This instance has now weight, they are just seeting file
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requirements.txt
CHANGED
@@ -1,7 +1,7 @@
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# Non-strict version lib
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-
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-
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-
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opencv-python
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transformers
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accelerate
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# Non-strict version lib
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torch==2.0.1
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torchaudio==2.0.1
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torchvision
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opencv-python
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transformers
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accelerate
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