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14235c42b9
* Remove yolov8 support from Frigate * Remove yolov8 from dev * Remove builds * Formatting and remove yolov5 * Fix lint * remove models download --------- Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
37 lines
1.3 KiB
Python
37 lines
1.3 KiB
Python
import logging
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import cv2
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import numpy as np
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logger = logging.getLogger(__name__)
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def preprocess(tensor_input, model_input_shape, model_input_element_type):
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model_input_shape = tuple(model_input_shape)
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assert tensor_input.dtype == np.uint8, f"tensor_input.dtype: {tensor_input.dtype}"
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if len(tensor_input.shape) == 3:
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tensor_input = tensor_input[np.newaxis, :]
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if model_input_element_type == np.uint8:
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# nothing to do for uint8 model input
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assert (
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model_input_shape == tensor_input.shape
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), f"model_input_shape: {model_input_shape}, tensor_input.shape: {tensor_input.shape}"
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return tensor_input
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assert (
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model_input_element_type == np.float32
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), f"model_input_element_type: {model_input_element_type}"
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# tensor_input must be nhwc
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assert tensor_input.shape[3] == 3, f"tensor_input.shape: {tensor_input.shape}"
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if tensor_input.shape[1:3] != model_input_shape[2:4]:
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logger.warn(
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f"preprocess: tensor_input.shape {tensor_input.shape} and model_input_shape {model_input_shape} do not match!"
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)
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# cv2.dnn.blobFromImage is faster than numpying it
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return cv2.dnn.blobFromImage(
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tensor_input[0],
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1.0 / 255,
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(model_input_shape[3], model_input_shape[2]),
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None,
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swapRB=False,
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)
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