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        Set window increase
                        For samples that are longer than the window length, a sliding window is used to classify the data multiple times.
                        This setting determines the increase of the sliding window in milliseconds, for each step.
                        This affects both live classification and model testing.
                    
                Add existing data
Upload data
                            You can upload CBOR, JSON, CSV, Parquet, WAV, JPG, PNG, AVI or MP4 files. You can also upload an annotation file named "info.labels"
                            with your data to assign bounding boxes, labels, and/or metadata.
                            View Uploader docs to learn more.
                            Alternatively, you can use our
                            Python SDK
                            to programmatically ingest data in various formats, such as pandas or numpy;
                            or import data directly from another project.
                            
For CSV and Parquet files, configure the CSV Wizard to define how your files should be processed before uploading files.
                    For CSV and Parquet files, configure the CSV Wizard to define how your files should be processed before uploading files.
                            Bounding boxes: You can upload object detection datasets in
                            any supported format.
                            Select both your images and the label file(s) when uploading to apply the labels.
                        
                    
                                    Upload mode
                                
                                
                                    Select files
                                    
                                
                                
                                        Using the info.labels file for labels and category.
                                    
                                Image label format
                                        
                
                                        Labeling method
                                            
                                        
                                            Annotations in this format could not be found in the selected files.
                                            Select both your images and any label files when uploading to apply the labels.
                                        
                
                                        
                                                A label map file could not be detected.
                                                This format requires a label map file, which maps keys to the label they represent.
                                                You can fix these labels later by clicking 'Edit labels' on the data acquisition page.
                                            
                                        Upload into category
                
                                        
                                                Upload category will be derived from the structure of your dataset
                                                (e.g. samples in a 'train' directory will be uploaded into training data).
                                            
                                        Label
                                        
                                                    You need to specify a label
                                                
                                            Advanced settings
                                    
                                        
                                            
                                        
                                        
                                            This dataset format uses bounding box labeling, used for object detection.
                                            
                                        
                                    
                                    
                                        
                                            
                                        
                                        
                                            This dataset format uses one label per sample. You may wish to change your project
                                            labeling method to 'one label per data item' in the project dashboard.
                                        
                                    
                                Upload output
Click 'Upload data' to begin
                                Upload data - contact us
                            Please give us some information about the data you are trying to upload.
                        
                    
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                        Import data from an existing project
                        This will copy all data from the project into this project. Data that was already imported will be skipped.
                    
                    Select project
Import progress
Collect new data
Collect data directly from your phone, computer, device, or development board.
                    Scan QR code to connect to your phone
                                Collect new data
Device "" is now connected
                            Use the 'Classify new data' section to collect data from this device.
                        
                    Connect your device or development board
                            You can connect almost any device over serial using our
                            data forwarder:
                        
                    $ edge-impulse-data-forwarder
                            Or connect a supported
                            device or development board:
                        
                    
                    Search supported development boards
                
            Send us your feedback!
                        We're always looking for ways to improve Edge Impulse. If you have any feedback, please let us know!
                    
                
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