Easy training on custom dataset. Various backends (MobileNet and SqueezeNet) supported. A YOLO demo to detect raccoon run entirely in brower is accessible at https://git.io/vF7vI (not on Windows).
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FileNotFoundError: [WinError 3] The system cannot find the path specified #334
In running the code of "keras-yolo2/Yolo Step-by-Step.ipynb" in Windows Jupyter environment, I got the following error:
FileNotFoundError: [WinError 3] The system cannot find the path specified: 'C:\Users\Yufeng2/logs/'
Here is the code cell that caused the error:
tbcounter = len([log for log in os.listdir(os.path.expanduser('~/logs/')) if 'coco' in log]) + 1 tensorboard = TensorBoard(logdir=os.path.expanduser('~/logs/') + 'coco' + '_' + str(tb_counter), histogram_freq=0, write_graph=True, write_images=False)
optimizer = Adam(lr=0.5e-4, beta_1=0.9, beta_2=0.999, epsilon=1e-08, decay=0.0)
optimizer = SGD(lr=1e-4, decay=0.0005, momentum=0.9)
optimizer = RMSprop(lr=1e-4, rho=0.9, epsilon=1e-08, decay=0.0)
model.compile(loss=custom_loss, optimizer=optimizer)
model.fit_generator(generator = train_batch, steps_per_epoch = len(train_batch), epochs = 100, verbose = 1, validation_data = valid_batch, validation_steps = len(valid_batch), callbacks = [early_stop, checkpoint, tensorboard], max_queue_size = 3)
Appreciate any advice.