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Running
on
A10G
Commit
•
e6c7107
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Parent(s):
89932ef
Update requirements.txt (#14)
Browse files- Update requirements.txt (741cfed93a39c40b3fbc6e2c3054bcc7c7712794)
- Update app.py (217632b709fc80599647648959f5fd2d61ea8068)
- Update app.py (8d6b2bfa051de3dbb4ee9370d830567350ea09dc)
- app.py +3 -4
- requirements.txt +4 -2
app.py
CHANGED
@@ -2,7 +2,7 @@ import gradio as gr
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import torch
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from PIL import Image
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-
from
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def main(
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input_im,
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@@ -21,7 +21,7 @@ def main(
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)
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images = []
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-
for i, image in enumerate(images_list["
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if(images_list["nsfw_content_detected"][i]):
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safe_image = Image.open(r"unsafe.png")
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images.append(safe_image)
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@@ -57,9 +57,8 @@ More details on the method and training will come in a future blog post.
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"""
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device = "cuda" if torch.cuda.is_available() else "cpu"
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-
pipe =
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"lambdalabs/sd-image-variations-diffusers",
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-
revision="273115e88df42350019ef4d628265b8c29ef4af5",
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)
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pipe = pipe.to(device)
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import torch
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from PIL import Image
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from diffusers import StableDiffusionImageVariationPipeline
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def main(
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input_im,
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)
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images = []
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for i, image in enumerate(images_list["images"]):
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if(images_list["nsfw_content_detected"][i]):
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safe_image = Image.open(r"unsafe.png")
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images.append(safe_image)
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"""
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device = "cuda" if torch.cuda.is_available() else "cpu"
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pipe = StableDiffusionImageVariationPipeline.from_pretrained(
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"lambdalabs/sd-image-variations-diffusers",
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)
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pipe = pipe.to(device)
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requirements.txt
CHANGED
@@ -1,3 +1,5 @@
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-
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--extra-index-url https://download.pytorch.org/whl/cu113
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-
torch
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+
diffusers
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transformers
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--extra-index-url https://download.pytorch.org/whl/cu113
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+
torch
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+
torchvision
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