initial commit

Dockerfile

@@ -0,0 +1,24 @@
+FROM python:3.9
+
+WORKDIR /code
+
+COPY ./requirements.txt /code/requirements.txt
+
+RUN apt-get update && apt-get upgrade -y && apt-get install -y libgl1-mesa-dev
+RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt
+
+# Set up a new user named "user" with user ID 1000
+RUN useradd -m -u 1000 user
+# Switch to the "user" user
+USER user
+# Set home to the user's home directory
+ENV HOME=/home/user \
+    PATH=/home/user/.local/bin:$PATH
+
+# Set the working directory to the user's home directory
+WORKDIR $HOME/app
+
+# Copy the current directory contents into the container at $HOME/app setting the owner to the user
+COPY --chown=user . $HOME/app
+
+CMD ["python", "app.py"]

README.md

@@ -3,7 +3,7 @@ title: ImageNet Hard Browser
 emoji: 🐨
 colorFrom: red
 colorTo: gray
-sdk: gradio
+sdk: docker
 sdk_version: 3.24.1
 app_file: app.py
 pinned: false

app.py

@@ -0,0 +1,26 @@
+import fiftyone as fo
+from io import BytesIO
+from PIL import Image
+from datasets import load_dataset
+import os
+
+# Load the dataset
+imagenet_hard_dataset = load_dataset("taesiri/imagenet-hard", split="validation")
+
+# same every image on disk and save path in a list
+
+os.makedirs("dataset", exist_ok=True)
+
+list_of_images = []
+
+for i in range(len(imagenet_hard_dataset)):
+    image = imagenet_hard_dataset[i]["image"].convert("RGB")
+    image.save(f"dataset/{i}.JPEG", "JPEG", quality=100)
+    list_of_images.append(f"imagenet_hard_images/{i}.jpg")
+
+
+if __name__ == "__main__":
+    # Ensures that the App processes are safely launched on Windows
+    dataset = fo.Dataset.from_images_dir("./dataset/")
+    session = fo.launch_app(dataset, port=7860)
+    session.wait()

requirements.txt

@@ -0,0 +1,5 @@
+fiftyone
+transformers
+datasets
+tqdm
+numpy