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load_screen

sleap_nn.config_generator.tui.screens.load_screen

Load data screen for the config generator TUI.

Step 1: Load and analyze an SLP file.

Classes:

Name Description
DatasetSummary

Widget to display dataset statistics summary.
LoadScreen

Screen for loading and analyzing SLP files.

DatasetSummary

Bases: Static

Widget to display dataset statistics summary.

Methods:

Name Description
__init__

Initialize with optional state.
render

Render the dataset summary.
update_state

Update with new state.
Source code in sleap_nn/config_generator/tui/screens/load_screen.py 
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class DatasetSummary(Static):
    """Widget to display dataset statistics summary."""

    def __init__(self, state: Optional[ConfigState] = None, **kwargs):
        """Initialize with optional state."""
        super().__init__(**kwargs)
        self._state = state

    def update_state(self, state: ConfigState) -> None:
        """Update with new state."""
        self._state = state
        self.refresh()

    def render(self) -> str:
        """Render the dataset summary."""
        if self._state is None:
            return "[dim]No data loaded[/dim]"

        stats = self._state.stats
        lines = [
            "[bold cyan]Dataset Summary[/bold cyan]",
            "",
            f"[bold]File:[/bold] {Path(stats.slp_path).name}",
            f"[bold]Labeled frames:[/bold] {stats.num_labeled_frames:,}",
            f"[bold]Total instances:[/bold] {stats.total_instances:,}",
            f"[bold]Videos:[/bold] {stats.num_videos}",
            "",
            f"[bold]Image size:[/bold] {stats.max_width}x{stats.max_height} "
            f"({'grayscale' if stats.is_grayscale else 'RGB'})",
            "",
            f"[bold]Max instances/frame:[/bold] {stats.max_instances_per_frame}",
            f"[bold]Avg instances/frame:[/bold] {stats.avg_instances_per_frame:.1f}",
            f"[bold]Max bbox size:[/bold] {stats.max_bbox_size:.0f}px",
            f"[bold]Avg bbox size:[/bold] {stats.avg_bbox_size:.0f}px",
            "",
            f"[bold]Skeleton:[/bold] {stats.num_nodes} nodes, {stats.num_edges} edges",
            f"[bold]Tracks:[/bold] {stats.num_tracks if stats.has_tracks else 'none'}",
        ]

        # Add data-based recommendation hint
        if stats.is_single_instance:
            lines.append("")
            lines.append("[green]Single animal detected[/green]")
        else:
            lines.append("")
            animal_pct = stats.animal_to_frame_ratio * 100
            overlap_pct = stats.overlap_frequency * 100
            if animal_pct < 20:
                lines.append(
                    f"[yellow]Small animals (~{animal_pct:.0f}% of frame)[/yellow]"
                )
            else:
                lines.append(
                    f"[yellow]Large animals (~{animal_pct:.0f}% of frame)[/yellow]"
                )
            lines.append(f"[yellow]Overlap frequency: {overlap_pct:.1f}%[/yellow]")

        return "\n".join(lines)

__init__(state=None, **kwargs)

Initialize with optional state.

Source code in sleap_nn/config_generator/tui/screens/load_screen.py 
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def __init__(self, state: Optional[ConfigState] = None, **kwargs):
    """Initialize with optional state."""
    super().__init__(**kwargs)
    self._state = state

render()

Render the dataset summary.

Source code in sleap_nn/config_generator/tui/screens/load_screen.py 
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def render(self) -> str:
    """Render the dataset summary."""
    if self._state is None:
        return "[dim]No data loaded[/dim]"

    stats = self._state.stats
    lines = [
        "[bold cyan]Dataset Summary[/bold cyan]",
        "",
        f"[bold]File:[/bold] {Path(stats.slp_path).name}",
        f"[bold]Labeled frames:[/bold] {stats.num_labeled_frames:,}",
        f"[bold]Total instances:[/bold] {stats.total_instances:,}",
        f"[bold]Videos:[/bold] {stats.num_videos}",
        "",
        f"[bold]Image size:[/bold] {stats.max_width}x{stats.max_height} "
        f"({'grayscale' if stats.is_grayscale else 'RGB'})",
        "",
        f"[bold]Max instances/frame:[/bold] {stats.max_instances_per_frame}",
        f"[bold]Avg instances/frame:[/bold] {stats.avg_instances_per_frame:.1f}",
        f"[bold]Max bbox size:[/bold] {stats.max_bbox_size:.0f}px",
        f"[bold]Avg bbox size:[/bold] {stats.avg_bbox_size:.0f}px",
        "",
        f"[bold]Skeleton:[/bold] {stats.num_nodes} nodes, {stats.num_edges} edges",
        f"[bold]Tracks:[/bold] {stats.num_tracks if stats.has_tracks else 'none'}",
    ]

    # Add data-based recommendation hint
    if stats.is_single_instance:
        lines.append("")
        lines.append("[green]Single animal detected[/green]")
    else:
        lines.append("")
        animal_pct = stats.animal_to_frame_ratio * 100
        overlap_pct = stats.overlap_frequency * 100
        if animal_pct < 20:
            lines.append(
                f"[yellow]Small animals (~{animal_pct:.0f}% of frame)[/yellow]"
            )
        else:
            lines.append(
                f"[yellow]Large animals (~{animal_pct:.0f}% of frame)[/yellow]"
            )
        lines.append(f"[yellow]Overlap frequency: {overlap_pct:.1f}%[/yellow]")

    return "\n".join(lines)

update_state(state)

Update with new state.

Source code in sleap_nn/config_generator/tui/screens/load_screen.py 
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def update_state(self, state: ConfigState) -> None:
    """Update with new state."""
    self._state = state
    self.refresh()

LoadScreen

Bases: Widget

Screen for loading and analyzing SLP files.

Classes:

Name Description
FileLoaded

Message sent when a file is loaded.

Methods:

Name Description
__init__

Initialize the load screen.
compose

Compose the screen layout.
handle_input_submit

Handle Enter key in input field.
on_mount

Handle mount - update summary if state exists.
Source code in sleap_nn/config_generator/tui/screens/load_screen.py 
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class LoadScreen(Widget):
    """Screen for loading and analyzing SLP files."""

    DEFAULT_CSS = """
    LoadScreen {
        width: 100%;
        height: 100%;
        padding: 1;
    }

    #load-container {
        width: 100%;
        height: auto;
    }

    #file-input-group {
        width: 100%;
        height: auto;
        padding: 1;
    }

    #file-input {
        width: 1fr;
    }

    #browse-btn {
        min-width: 12;
        margin-left: 1;
    }

    #summary-container {
        width: 100%;
        height: auto;
        margin-top: 2;
    }

    #dataset-summary {
        background: $panel;
        border: solid $primary;
        padding: 1 2;
        min-height: 15;
    }

    """

    class FileLoaded(Message):
        """Message sent when a file is loaded."""

        def __init__(self, state: ConfigState):
            """Initialize with the loaded state."""
            super().__init__()
            self.state = state

    def __init__(self, state: Optional[ConfigState] = None, **kwargs):
        """Initialize the load screen.

        Args:
            state: Optional existing ConfigState.
            **kwargs: Additional keyword arguments passed to parent.
        """
        super().__init__(**kwargs)
        self._state = state

    def compose(self) -> ComposeResult:
        """Compose the screen layout."""
        with Vertical(id="load-container"):
            yield Label(
                "[bold]Step 1: Dataset Overview[/bold]", classes="section-title"
            )

            if self._state:
                # File already loaded via CLI
                yield Label(
                    "Review your dataset statistics below, then proceed to "
                    "select a model type.",
                    classes="hint",
                )
            else:
                # No file provided, show input
                yield Label(
                    "Enter the path to your .slp file (SLEAP labels file)",
                    classes="hint",
                )

            with Horizontal(id="file-input-group"):
                yield Input(
                    placeholder="Path to .slp file... (press Enter to load)",
                    id="file-input",
                    value=str(self._state.slp_path) if self._state else "",
                )

            with Container(id="summary-container"):
                yield DatasetSummary(self._state, id="dataset-summary")

    def on_mount(self) -> None:
        """Handle mount - update summary if state exists."""
        if self._state is not None:
            summary = self.query_one("#dataset-summary", DatasetSummary)
            summary.update_state(self._state)

    @on(Input.Submitted, "#file-input")
    async def handle_input_submit(self, event: Input.Submitted) -> None:
        """Handle Enter key in input field."""
        file_input = self.query_one("#file-input", Input)
        path = file_input.value.strip()

        if not path:
            self.app.notify("Please enter a file path", severity="error")
            return

        path_obj = Path(path).expanduser().resolve()

        if not path_obj.exists():
            self.app.notify(f"File not found: {path}", severity="error")
            return

        if not path_obj.suffix.lower() in [".slp", ".h5"]:
            self.app.notify("Please select a .slp file", severity="error")
            return

        try:
            self.app.notify("Loading and analyzing file...")
            self._state = ConfigState(str(path_obj))

            # Trigger lazy loading of stats
            _ = self._state.stats

            # Update summary display
            summary = self.query_one("#dataset-summary", DatasetSummary)
            summary.update_state(self._state)

            # Auto-configure with defaults
            self._state.auto_configure()

            # Post message to parent app
            self.post_message(self.FileLoaded(self._state))

        except Exception as e:
            self.app.notify(f"Error loading file: {e}", severity="error")

FileLoaded

Bases: Message

Message sent when a file is loaded.

Methods:

Name Description
__init__

Initialize with the loaded state.
Source code in sleap_nn/config_generator/tui/screens/load_screen.py 
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class FileLoaded(Message):
    """Message sent when a file is loaded."""

    def __init__(self, state: ConfigState):
        """Initialize with the loaded state."""
        super().__init__()
        self.state = state
__init__(state)

Initialize with the loaded state.

Source code in sleap_nn/config_generator/tui/screens/load_screen.py 
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def __init__(self, state: ConfigState):
    """Initialize with the loaded state."""
    super().__init__()
    self.state = state

__init__(state=None, **kwargs)

Initialize the load screen.

Parameters:

Name Type Description Default
state Optional[ConfigState]

Optional existing ConfigState.

 None
**kwargs

Additional keyword arguments passed to parent.

 {}
Source code in sleap_nn/config_generator/tui/screens/load_screen.py 
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def __init__(self, state: Optional[ConfigState] = None, **kwargs):
    """Initialize the load screen.

    Args:
        state: Optional existing ConfigState.
        **kwargs: Additional keyword arguments passed to parent.
    """
    super().__init__(**kwargs)
    self._state = state

compose()

Compose the screen layout.

Source code in sleap_nn/config_generator/tui/screens/load_screen.py 
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def compose(self) -> ComposeResult:
    """Compose the screen layout."""
    with Vertical(id="load-container"):
        yield Label(
            "[bold]Step 1: Dataset Overview[/bold]", classes="section-title"
        )

        if self._state:
            # File already loaded via CLI
            yield Label(
                "Review your dataset statistics below, then proceed to "
                "select a model type.",
                classes="hint",
            )
        else:
            # No file provided, show input
            yield Label(
                "Enter the path to your .slp file (SLEAP labels file)",
                classes="hint",
            )

        with Horizontal(id="file-input-group"):
            yield Input(
                placeholder="Path to .slp file... (press Enter to load)",
                id="file-input",
                value=str(self._state.slp_path) if self._state else "",
            )

        with Container(id="summary-container"):
            yield DatasetSummary(self._state, id="dataset-summary")

handle_input_submit(event) async

Handle Enter key in input field.

Source code in sleap_nn/config_generator/tui/screens/load_screen.py 
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@on(Input.Submitted, "#file-input")
async def handle_input_submit(self, event: Input.Submitted) -> None:
    """Handle Enter key in input field."""
    file_input = self.query_one("#file-input", Input)
    path = file_input.value.strip()

    if not path:
        self.app.notify("Please enter a file path", severity="error")
        return

    path_obj = Path(path).expanduser().resolve()

    if not path_obj.exists():
        self.app.notify(f"File not found: {path}", severity="error")
        return

    if not path_obj.suffix.lower() in [".slp", ".h5"]:
        self.app.notify("Please select a .slp file", severity="error")
        return

    try:
        self.app.notify("Loading and analyzing file...")
        self._state = ConfigState(str(path_obj))

        # Trigger lazy loading of stats
        _ = self._state.stats

        # Update summary display
        summary = self.query_one("#dataset-summary", DatasetSummary)
        summary.update_state(self._state)

        # Auto-configure with defaults
        self._state.auto_configure()

        # Post message to parent app
        self.post_message(self.FileLoaded(self._state))

    except Exception as e:
        self.app.notify(f"Error loading file: {e}", severity="error")

on_mount()

Handle mount - update summary if state exists.

Source code in sleap_nn/config_generator/tui/screens/load_screen.py 
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def on_mount(self) -> None:
    """Handle mount - update summary if state exists."""
    if self._state is not None:
        summary = self.query_one("#dataset-summary", DatasetSummary)
        summary.update_state(self._state)