Moved to HF

README.md

@@ -1,18 +1,31 @@
+---
+title: Albumentations Demo
+emoji: 🏢
+colorFrom: blue
+colorTo: pink
+sdk: streamlit
+sdk_version: 1.22.0
+app_file: "src/app.py"
+pinned: true
+license: mit
+short_description: "Optimize image augmentations with Albumentations"
+tags: ["Computer Vision", "Image Augmentation", "Albumentations", "Streamlit", "Image Processing", "CV", "Image", "Augmentation"]
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+
 # albumentations-demo
 
 This service is created to demonstrate abilities of the [Albumentations](https://github.com/albumentations-team/albumentations) - a library for efficient image augmentations.
-[Link to my article about augmentations selection and why this service can be useful](https://towardsdatascience.com/explore-image-augmentations-using-a-convenient-tool-a199b4ac8214)
-
-## Easy start
-I don't actively support this tool anymore but you can run it locally or use one of the deployed instances. 
 
-If you would like to run the service locally follow the installation instruction.
+[Link to my article about augmentations selection and why this service can be useful](https://towardsdatascience.com/explore-image-augmentations-using-a-convenient-tool-a199b4ac8214)
 
-You can find the online version of this tool here: [https://albumentations-demo.herokuapp.com/](https://albumentations-demo.herokuapp.com/) (it will be stopped soon).
+Project repository: [github.com/IliaLarchenko/albumentations-demo](https://github.com/IliaLarchenko/albumentations-demo)
 
-It is also deployed as a Hugging Face space: [https://huggingface.co/spaces/ilarchenko/albumentations-demo](https://huggingface.co/spaces/ilarchenko/albumentations-demo)
+Online demo: [huggingface.co/spaces/IliaLarchenko/albumentations-demo](https://huggingface.co/spaces/IliaLarchenko/albumentations-demo)
 
-As alternative you can use the fork supported and deployed by the Albumentations team [https://demo.albumentations.ai/](https://demo.albumentations.ai/)
+## Easy start
+If you would like to run the service locally follow the installation instruction.
 
 ## Installation and run
 ```

requirements.txt

@@ -1,3 +1,3 @@
 albumentations==0.4.3
 altair==4.0
-streamlit==1.10
+streamlit==1.22.0

src/app.py

@@ -68,9 +68,6 @@ def main():
                 # show title
                 st.title("Demo of Albumentations")
 
-                st.write("I have deployed this service as a Hugging Face Space: https://huggingface.co/spaces/ilarchenko/albumentations-demo please, check it out!")
-                st.write("The version deployed here on Heroku will be deprecated soon.")
-
                 # show the images
                 width_transformed = int(
                     width_original / image.shape[1] * augmented_image.shape[1]

src/utils.py

@@ -7,7 +7,7 @@ import argparse
 import streamlit as st
 
 
-@st.cache
+@st.cache_data
 def get_arguments():
     """Return the values of CLI params"""
     parser = argparse.ArgumentParser()
@@ -17,7 +17,7 @@ def get_arguments():
     return getattr(args, "image_folder"), getattr(args, "image_width")
 
 
-@st.cache
+@st.cache_data
 def get_images_list(path_to_folder: str) -> list:
     """Return the list of images from folder
     Args:
@@ -29,7 +29,7 @@ def get_images_list(path_to_folder: str) -> list:
     return image_names_list
 
 
-@st.cache
+@st.cache_data
 def load_image(image_name: str, path_to_folder: str, bgr2rgb: bool = True):
     """Load the image
     Args:
@@ -58,7 +58,7 @@ def upload_image(bgr2rgb: bool = True):
     return image
 
 
-@st.cache
+@st.cache_data
 def load_augmentations_config(
     placeholder_params: dict, path_to_config: str = "configs/augmentations.json"
 ) -> dict: