121 lines
4.0 KiB
Python
121 lines
4.0 KiB
Python
from vision.model import Image
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from typing import List
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import numpy as np
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import vision.descriptor.avg_RGB as rgb
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import vision.util.edge as edge
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import logging
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logger = logging.getLogger(__name__)
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def grid_image(height: int, width: int, pixels: np.array):
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shape = pixels.shape
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segments = []
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for i in range(height):
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for j in range(width):
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row_start = round(i * shape[0] / height)
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row_end = round((i+1) * shape[0] / height)
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column_start = round(j * shape[1] / width)
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column_end = round((j + 1) * shape[1] / width)
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segments.append(pixels[row_start:row_end, column_start:column_end, :])
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return segments
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def extract_spatial_texture(height: int,
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width: int,
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bins: int,
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threshold: float,
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pixels: np.array = None,
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image: Image = None,
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images: List[Image] = None):
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if pixels is None and image is None and images is None:
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raise KeyError('no image provided')
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def extract(i):
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segments = grid_image(height, width, i)
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descriptor = np.array([])
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for seg in segments:
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img_edge = edge.get_edge_info(pixels=seg)
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hist = edge.get_edge_angle_hist(img_edge, bins=bins, threshold=threshold)
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descriptor = np.append(descriptor, hist)
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return descriptor
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if images is not None:
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length = len(images)
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for index, image in enumerate(images):
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logger.debug(f'generating {index} of {length}')
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image.descriptor = extract(image.pixels)
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return
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elif image is not None:
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image.descriptor = extract(image.pixels)
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else:
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return extract(pixels)
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def extract_spatial_average_rgb(height: int,
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width: int,
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pixels: np.array = None,
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image: Image = None,
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images: List[Image] = None):
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if pixels is None and image is None and images is None:
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raise KeyError('no image provided')
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def extract(i):
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segments = grid_image(height, width, i)
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descriptor = np.array([])
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for seg in segments:
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descriptor = np.append(descriptor, rgb.extract_average_rgb(pixels=seg))
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return descriptor
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if images is not None:
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length = len(images)
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for index, image in enumerate(images):
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logger.debug(f'generating {index} of {length}')
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image.descriptor = extract(image.pixels)
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return
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elif image is not None:
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image.descriptor = extract(image.pixels)
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else:
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return extract(pixels)
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def extract_spatial_avg_rgb_texture(height: int,
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width: int,
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bins: int,
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threshold: float,
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pixels: np.array = None,
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image: Image = None,
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images: List[Image] = None):
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if pixels is None and image is None and images is None:
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raise KeyError('no image provided')
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def extract(i):
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segments = grid_image(height, width, i)
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descriptor = np.array([])
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for seg in segments:
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img_edge = edge.get_edge_info(pixels=seg)
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hist = edge.get_edge_angle_hist(img_edge, bins=bins, threshold=threshold)
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descriptor = np.append(descriptor, hist)
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descriptor = np.append(descriptor, rgb.extract_average_rgb(pixels=seg))
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return descriptor
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if images is not None:
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length = len(images)
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for index, image in enumerate(images):
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logger.debug(f'generating {index} of {length}')
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image.descriptor = extract(image.pixels)
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return
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elif image is not None:
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image.descriptor = extract(image.pixels)
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else:
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return extract(pixels)
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