24 lines
715 B
Python
24 lines
715 B
Python
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import numpy as np
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import cv2
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import cupy as cp
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# Load the image and convert it to a NumPy array
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image = cv2.imread("fruits.jpg")
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image = image.astype(np.float32)
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# Use cupy to transfer the image to the GPU
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image_gpu = cp.asarray(image)
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# Perform k-means clustering on the GPU
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cluster_centers_gpu, labels_gpu, _ = cp.cluster.kmeans(image_gpu.reshape(-1, 3), k=8)
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# Transfer the cluster centers and labels back to the CPU
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cluster_centers = cp.asnumpy(cluster_centers_gpu)
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labels = cp.asnumpy(labels_gpu)
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# Convert the image pixels to the closest cluster
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clustered_image = cluster_centers[labels].reshape(image.shape)
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# Save the clustered image as a PNG file
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cv2.imwrite("clustered_image.png", clustered_image)
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