197 lines
6.2 KiB
Python
197 lines
6.2 KiB
Python
# -*- coding: utf-8 -*-
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import io
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import logging
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import time
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from abc import ABCMeta, abstractmethod
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from collections import namedtuple
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from types import TracebackType
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from typing import BinaryIO, List, Optional, Tuple, Type, Union
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from labthings import ClientEvent, StrictLock
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# Class to store a frames metadata
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TrackerFrame = namedtuple("TrackerFrame", ["size", "time"])
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class FrameStream(io.BytesIO):
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"""
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A file-like object used to analyse and stream MJPEG frames.
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Instead of analysing a load of real MJPEG frames
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after they've been stored in a BytesIO stream,
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we tell the camera to write frames to this class instead.
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We then do analysis as the frames are written, and discard
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old frames as each new frame is written.
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"""
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def __init__(self, *args, **kwargs):
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# Array of TrackerFrame objects
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io.BytesIO.__init__(self, *args, **kwargs)
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# Array of TrackerFramer objects
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self.frames: List[TrackerFrame] = []
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# Last acquired TrackerFramer object
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self.last: Optional[TrackerFrame] = None
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# Are we currently tracking frame sizes?
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self.tracking: bool = False
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# Event to track if a new frame is available since the last getvalue() call
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# We use a ClientEvent so that each thread can call getvalue() independantly
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self.new_frame: ClientEvent = ClientEvent()
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def __enter__(self):
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self.start_tracking()
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return super().__enter__()
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def __exit__(
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self,
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t: Optional[Type[BaseException]],
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value: Optional[BaseException],
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traceback: Optional[TracebackType],
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) -> Optional[bool]:
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self.stop_tracking()
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return super().__exit__(t, value, traceback)
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def start_tracking(self):
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"""Start tracking frame sizes"""
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if not self.tracking:
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logging.debug("Started tracking frame data")
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self.tracking = True
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def stop_tracking(self):
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"""Stop tracking frame sizes"""
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if self.tracking:
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logging.debug("Stopped tracking frame data")
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self.tracking = False
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def reset_tracking(self):
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"""Empty the array of tracked frame sizes"""
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self.frames = []
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def write(self, s):
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"""
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Write a new frame to the FrameStream. Does a few things:
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1. If tracking frame size, store the size in self.frames
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2. Rewind and truncate the stream (delete previous frame)
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3. Store the new frame image
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4. Set the new_frame event
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"""
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if self.tracking:
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frame = TrackerFrame(size=len(s), time=time.time())
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self.frames.append(frame)
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self.last = frame
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# Reset the stream for the next frame
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super().seek(0)
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super().truncate()
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# Write the new frame
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super().write(s)
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# Set the new frame event
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self.new_frame.set()
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def getvalue(self) -> bytes:
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"""Clear tne new_frame event and return frame data"""
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self.new_frame.clear()
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return super().getvalue()
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def getframe(self) -> bytes:
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"""Wait for a new frame to be available, then return it"""
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self.new_frame.wait()
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return self.getvalue()
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class BaseCamera(metaclass=ABCMeta):
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"""
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Base implementation of StreamingCamera.
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"""
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def __init__(self):
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#: :py:class:`labthings.StrictLock`: Access lock for the camera
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self.lock: StrictLock = StrictLock(name="Camera", timeout=None)
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#: :py:class:`FrameStream`: Streaming and analysis frame buffer
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self.stream: FrameStream = FrameStream()
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self.stream_active: bool = False
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self.record_active: bool = False
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self.preview_active: bool = False
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self.image_resolution: Tuple[int, int] = (1312, 976)
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self.stream_resolution: Tuple[int, int] = (640, 480)
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@property
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@abstractmethod
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def configuration(self):
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"""The current camera configuration."""
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@property
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@abstractmethod
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def state(self):
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"""The current read-only camera state."""
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@property
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def settings(self):
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return self.read_settings()
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@abstractmethod
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def start_stream(self):
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"""Ensure the frame stream is actively running"""
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@abstractmethod
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def stop_stream(self):
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"""Stop the active stream, if possible"""
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@abstractmethod
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def update_settings(self, config: dict):
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"""Update settings from a config dictionary"""
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@abstractmethod
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def read_settings(self) -> dict:
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"""Return the current settings as a dictionary"""
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@abstractmethod
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def capture(
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self,
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output: Union[str, BinaryIO],
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fmt: str = "jpeg",
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use_video_port: bool = False,
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resize: Optional[Tuple[int, int]] = None,
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bayer: bool = True,
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thumbnail: Optional[Tuple[int, int, int]] = None,
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):
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"""
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Perform a basic capture to output
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Args:
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output: String or file-like object to write capture data to
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fmt: Format of the capture.
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use_video_port: Capture from the video port used for streaming. Lower resolution, faster.
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resize: Resize the captured image.
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bayer: Store raw bayer data in capture
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thumbnail: Dimensions and quality (x, y, quality) of a thumbnail to generate, if supported
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"""
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def start_worker(self, **_) -> bool:
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"""Start the background camera thread if it isn't running yet."""
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logging.debug(
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"`start_worker` method has been deprecated and is no longer required. Please avoid calling this method."
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)
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return True
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def get_frame(self):
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"""Return the current camera frame."""
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logging.debug(
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"`camera.get_frame` method has been deprecated. Please use `camera.stream.getframe()."
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)
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return self.stream.getframe()
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def __enter__(self):
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"""Create camera on context enter."""
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return self
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def __exit__(self, exc_type, exc_value, traceback):
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"""Close camera stream on context exit."""
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self.close()
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def close(self):
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"""Close the BaseCamera and all attached StreamObjects."""
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logging.info("Closed %s", (self))
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