Cellpose-SAM

概要

これまでと少しコードが変わってくるので注意。

MacでもGPUデバイスを指定する必要がなくなった

準備

code:Anaconda Prompt

pip install --upgrade cellpose

Sample code

code:jupyter notebook

import os

import numpy as np

import matplotlib.pyplot as plt

from tqdm.notebook import tqdm

from cellpose import models, io, utils, plot,core

import pandas as pd

import torch

print(core.use_gpu())

code:jupyter notebook

print(f"Image shape: {images.shape}")

plt.title('First timepoint')

plt.colorbar()

plt.show()

code:jupyter notebook

%%time

model = models.CellposeModel(gpu=False)

fig = plt.figure(figsize=(16, 10))

plt.tight_layout()

plt.show()

code:jupyter notebook

%%time

model = models.CellposeModel(gpu=True)

fig = plt.figure(figsize=(16, 10))

plt.tight_layout()

plt.show()

code:jupyter notebook

%%time

batch_size = 10

num_batches = (len(images) + batch_size - 1) // batch_size

model = models.CellposeModel(gpu=True)

masks = []

for b in tqdm(range(num_batches), desc="Processing batches"):

start_idx = b * batch_size

end_idx = min((b + 1) * batch_size, len(images))

for i, img in enumerate(tqdm(batch_images, desc=f"Batch {b+1}/{num_batches}", leave=False)):

mask, flow, style = model.eval(img,flow_threshold=0.4,cellprob_threshold=0.0)

masks.append(mask)

io.save_to_png(img, mask, flow, 'segmentation/'+str(i)+'.png')

2025/5/20