Metadata-Version: 2.1
Name: stereo-mideval
Version: 1.0.8
Summary: Evaluation dataset and tools from Middlebury Stereo Evaulation data 2014.
Home-page: https://github.com/i3drobotics/stereomideval
Author: Ben Knight
Author-email: bknight@i3drobotics.com
License: UNKNOWN
Description: # stereo-mideval
        Python package for evaluation dataset and tools from the [Middlebury stereo evaulation 2014](https://vision.middlebury.edu/stereo/data/scenes2014/) dataset.
        This project is in development by [I3DR](https://i3drobotics.com/) for evaluation stereo matching algorithms for use in stereo cameras. However this is project is fully open-source with no limitations to encorage and support others who may need access to this tools. 
        
        ## Install
        ```
        pip install stereo-mideval
        ```
        
        # Features
        - Download scene data from Middlebury servers
        - Load disparity image and stereo pair from scene data
        - Display normalised colormaped disparity image
        - Convert disparity image to depth image using calibration file from scene data
        
        # Examples
        ## Download and display scene data
        ```python
        import os
        from stereomideval import Dataset
        
        # Path to dowmload datasets
        dataset_folder = os.path.join(os.getcwd(),"datasets") 
        
        # Create dataset folder
        if not os.path.exists(dataset_folder):
            os.makedirs(dataset_folder)
        
        # Initalise stereomideval Dataset object
        stmid_dataset = Dataset()
        
        # Get list of scene in dataset (2014) and iterate through them
        for scenename in stmid_dataset.get_scene_list():
            # Download dataset from middlebury servers
            # will only download it if it hasn't already been downloaded
            print("Downloading data for scene '"+scenename+"'...")
            stmid_dataset.download_scene_data(scenename,dataset_folder) 
            # Load scene data from downloaded folder
            print("Loading data for scene '"+scenename+"'...")
            scene_data = stmid_dataset.load_scene_data(scenename,dataset_folder,True)
        ```
        
        ## Developement
        ### Upcomming features
        - Evaluation of disparity image compared to ground truth disparity
        - Evaulation of depth image compared to ground truth depth for real-world error metrics
        
        ### Build
        ```
        python -m pip install --user --upgrade twine wheel && python setup.py clean --all && python setup.py sdist bdist_wheel
        ```
        
        ### Upload to Test Pip
        Test pip package is maintained by user: [i3DR](https://pypi.org/user/i3DR/)
        ```
        python -m twine upload --repository-url https://test.pypi.org/legacy/ dist/*
        ```
        
        ### Upload to Pip
        Pip package is maintained by user: [i3DR](https://pypi.org/user/i3DR/)
        ```
        python -m twine upload dist/*
        ```
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.5
Description-Content-Type: text/markdown
