update

beit_base_patch16_224_pt22k_ft22k/Dockerfile

@@ -0,0 +1,25 @@
+# please visit https://github.com/xfyun/aiges/releases to get stable and suitable iamges.
+
+FROM docker.io/library/python:3.8.9
+
+
+RUN sed -i 's/deb.debian.org/mirrors.ustc.edu.cn/g' /etc/apt/sources.list
+RUN sed -i 's|security.debian.org/debian-security|mirrors.ustc.edu.cn/debian-security|g' /etc/apt/sources.list
+
+
+WORKDIR /home/user/app
+RUN useradd -m -u 1000 user
+RUN chown  -R 1000.1000 /home/user
+
+
+RUN pip config set global.index-url https://pypi.mirrors.ustc.edu.cn/simple/
+
+
+RUN pip install --no-cache-dir pip==22.3.1
+RUN --mount=target=requirements.txt,source=requirements.txt 	pip install --no-cache-dir -r requirements.txt
+
+
+COPY --chown=1000 ./ /home/user/app
+
+
+CMD ["python3", "app.py"]

beit_base_patch16_224_pt22k_ft22k/app.py

@@ -1,5 +1,4 @@
 import gradio as gr
-from PIL import Image
 from transformers import BeitImageProcessor, BeitForImageClassification
 
 
@@ -18,10 +17,11 @@ def inference(img):
 
     return model.config.id2label[predicted_class_idx]
 
+
 title = "Image classification:beit-base-patch16-224-pt22k-ft22k"
 description = "Gradio Demo for beit-base-patch16-224-pt22k-ft22k. To use it, simply upload your image, or click one of the examples to load them."
 article = "<p style='text-align: center'><a href='https://github.com/bryandlee/animegan2-pytorch' target='_blank'>Github Repo Pytorch</a></p> <center><img src='https://visitor-badge.glitch.me/badge?page_id=akhaliq_animegan' alt='visitor badge'></center></p>"
-examples=[['example_cat.jpg'],['Masahiro.png']]
+examples = [['example_cat.jpg'], ['Masahiro.png']]
 
 demo = gr.Interface(
     fn=inference,
@@ -34,31 +34,3 @@ demo = gr.Interface(
 
 demo.launch()
 
-
-##
-
-
-# model_dir = "hub/animegan2-pytorch-main"
-# model_dir_weight = "hub/checkpoints/face_paint_512_v1.pt"
-#
-# model2 = torch.hub.load(
-#     model_dir,
-#     "generator",
-#     pretrained=True,
-#     progress=False,
-#     source="local"
-# )
-# model1 = torch.load(model_dir_weight)
-# face2paint = torch.hub.load(
-#     model_dir, 'face2paint',
-#     size=512,side_by_side=False,
-#     source="local"
-# )
-#
-# def inference(img, ver):
-#     if ver == 'version 2 (🔺 robustness,🔻 stylization)':
-#         out = face2paint(model2, img)
-#     else:
-#         out = face2paint(model1, img)
-#     return out
-#

beit_base_patch16_224_pt22k_ft22k/requirements.txt

@@ -0,0 +1,2 @@
+gradio==3.21.0
+transformers==4.27.1