Accuracy cannot get more than 70%

Hi, I am new in deep learning. I need to train a network which is technically cell detection. cropped_jpg_55_199_0 cropped_png_55_199_0

I uploaded 2 images which are examples from my data set. Here I will also upload my program as well:data_gen_args = dict(rotation_range=0.2, width_shift_range=0.05, height_shift_range=0.05, shear_range=0.05, zoom_range=0.05, horizontal_flip=True, fill_mode='nearest') myGene = trainGenerator(2,'/Users/khand/OneDrive/Desktop/Thesis/Case_db/train_data','org','png',data_gen_args,save_to_dir = None) model = unet() model_checkpoint = ModelCheckpoint('unet_membrane.hdf5', monitor='loss',verbose=1, save_best_only=True) model.fit_generator(myGene,steps_per_epoch=100,epochs=10, callbacks=[model_checkpoint])

So if you have any suggestion how I can Improve my program in order to have higher accuracy. I would like to hear any ideas.

Is it possible to post your data and existing code somewhere? This would help significantly with giving suggestions on how to improve your setup.

This is code.
And I have data consisted of 480 images I can increase it to 560, and data is in two folders and the images I uploaded are in examples from folders.

Since this is the fastai forums, I would recommend using fastai. :grinning:
The code you shared uses Keras.

I see, could you share a source for me from where I get a code and implement it to my dataset ?

I would highly advice you to take the fastai course 2019 or at least watch lesson 3 which tackles the segmentation problem.

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