Created
July 12, 2017 10:30
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plots loss in keras, additionally plots segmentation in image
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#https://gist.github.com/stared/dfb4dfaf6d9a8501cd1cc8b8cb806d2e | |
class PlotLosses(keras.callbacks.Callback): | |
def __init__(self,imgs): | |
super(PlotLosses, self).__init__() | |
self.imgs=imgs | |
def on_train_begin(self, logs={}): | |
self.i = 0 | |
self.x = [] | |
self.losses = [] | |
self.val_losses = [] | |
self.fig = plt.figure() | |
self.logs = [] | |
def draw(self): | |
preds=model.predict(self.imgs[:1]) | |
plt.imshow(self.imgs[0]) | |
plt.imshow(np.argmax(preds.reshape([224,224,2]),axis=-1),alpha=0.6) | |
def on_batch_end(self,batch,logs={}): | |
clear_output(wait=True) | |
self.draw() | |
plt.show(); | |
def on_epoch_end(self, epoch, logs={}): | |
self.logs.append(logs) | |
self.x.append(self.i) | |
self.losses.append(logs.get('loss')) | |
self.val_losses.append(logs.get('val_loss')) | |
self.i += 1 | |
clear_output(wait=True) | |
plt.plot(self.x, self.losses, label="loss") | |
plt.plot(self.x, self.val_losses, label="val_loss") | |
plt.legend() | |
plt.show(); | |
#gidi | |
plot_losses = PlotLosses(imgs[:1]) |
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