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| title: test | |
| emoji: 🏆 | |
| colorFrom: green | |
| colorTo: purple | |
| sdk: gradio | |
| sdk_version: 5.30.0 | |
| 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 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 | |
| Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference |