Welcome to labvision’s documentation!¶
Lab vision provides a range of tools to collect, manipulate and store images / video.
Contents¶
Installation¶
The project can be installed and maintained using pip
Initial Installation¶
pip install git+https://github.com/MikeSmithLabTeam/labvision
Update¶
pip install –upgrade git+https://github.com/MikeSmithLabTeam/labvision
Camera¶
Camera contains classes for controlling webcams through opencv and digital cameras via the linux tool gphoto2. The timer provides a simple way to perform timelapse imaging.
Camera¶
Camera Config¶
Web camera settings All settings are accessible via self.cam_type in CameraBase class Only required settings are 1 resolution and 1 fps. Can add any optional info you want.
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labvision.camera.camera_config.MIKELAPTOP= {'fps': (20.0,), 'res': (640, 480, 3)}¶ Digital Camera settings Acquisition settings for digital cameras need their own script. See nikon_config.sh for example in scripts folder. You may need to change permissions to make this file executable.
Digtal Cameras¶
Quick Timer¶
Images¶
Images contains a host of methods for interacting with and manipulating images.
Basics¶
Contours¶
cropping¶
Draw¶
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labvision.images.draw.draw_filled_polygon(im, points, color=(0, 0, 255))¶ Adds a filled polygon to an image
Parameters: - im – np.ndarrary of dtype np.uint8
- points – N, 2 ndarray of corner points
- color – BGR color tuple or images library color
Returns: im: ndarray
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labvision.images.draw.draw_circle(im, cx, cy, rad, color=(0, 255, 255), thickness=2)¶ Draw Circle NEEDS DOCSTRING
Parameters: - im –
- cx –
- cy –
- rad –
- color –
- thickness –
Returns:
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labvision.images.draw.draw_circles(im, circles, color=(0, 255, 255), thickness=2)¶ NEEDS DOCSTRING
Parameters: - im –
- circles –
- color –
- thickness –
Returns:
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labvision.images.draw.draw_circles_with_scale(im, circles, values, cmap=<sphinx.ext.autodoc.importer._MockObject object>, thickness=2)¶ NEEDS DOCSTRING
Parameters: - im –
- circles –
- values –
- cmap –
- thickness –
Returns:
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labvision.images.draw.draw_delaunay_tess(im, points)¶ Draws the delaunay tesselation for a set of points on an image
Parameters: - im (input image) – Any number of channels
- points (array of N points) – Shape (N, 2). points[:, 0] contains x coordinates points[:, 1] contains y coordinates
Returns: in – Same shape and type as input image
Return type: annotated image
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labvision.images.draw.draw_polygon(im, vertices, color=(0, 0, 255), thickness=1)¶ Draws a polygon on an image from a list of vertices
Parameters: - im (input image) – Any number of channels
- vertices (array of N vertices) –
- Shape (N, 2) where
- vertices[:, 0] contains x coordinates vertices[:, 1] contains y coordinates
- color (BGR tuple) – if input image is grayscale then circles will be black
- thickness (int) – Thickness of the lines
Returns: out – Same shape and type as input image
Return type: output image
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labvision.images.draw.draw_polygons(im, polygons, color=(0, 0, 255))¶ Draws multiple polygons on an image from a list of polygons
Parameters: - im (input image) – Any number of channels
- polygons (array containing coordinates of polygons) – shape is (P, N, 2) where P is the number of polygons, N is the number of vertices in each polygon. [:, :, 0] contains x coordinates, [:, :, 1] contains y coordinates.
- color (BGR tuple) –
Returns: img – Same shape and type as input image
Return type: annotated image
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labvision.images.draw.draw_voronoi_cells(im, points)¶ Draws the voronoi cells for a set of points on an image
Parameters: - im (input image) – Any number of channels
- points (array of N points) – Shape (N, 2). points[:, 0] contains x coordinates points[:, 1] contains y coordinates
Returns: im – Same shape and type as input image
Return type: annotated image
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labvision.images.draw.draw_contours(im, contours, col=(0, 0, 255), thickness=1)¶ NEEDS DOCSTRING
Parameters: - im –
- contours –
- col –
- thickness –
Returns: