metadata
title: Indoor vs Outdoor Detection Leaderboard
emoji: 🏆
colorFrom: green
colorTo: purple
sdk: gradio
sdk_version: 5.49.1
app_file: app.py
pinned: false
Using the provided dataset can you create an accurate and fast Indoor vs Outdoor detection model?
Submission Format
Users must submit a Model Name and a Group Name:
-There cannot be two models with the same name in the same group.
-If a user tries to submit a model name that has already been used in their group, they must either change the group name or the model name,
otherwise they can overwrite the previous model and the better model will be chosen.
Users must submit their code in a .zip file format. The zip file should include:
-A main.py Python file that contains a function named evaluate.
-A user_reqs.txt file listing all dependencies.
Main Python File Requirements
-The file must be named main.py.
-The main Python script must contain a function named evaluate.
-This function should accept a single parameter: filepath, which represents the file path to the dataset.
-The function should process the dataset and return an array with a length of eight of 0s or 1s, indicating whether a sector is labelled inside or outside.
Requirements File
-The user_reqs.txt file must include all necessary dependencies required to run the submitted code.
Dataset
There is a dataset available to download here: https://huggingface.co/datasets/IndoorOutdoor/train_data/tree/main and here is a link to the ReadME that gives an overview of the dataset: https://huggingface.co/datasets/IndoorOutdoor/train_data/blob/main/README.md
Notes
-If the leaderboard looks incorrect after submission, or if there is an error in the status box, refresh the page to see the updated leaderboard.
Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference