FastAi How to turn off crop in ImageDataBunch

I just trained my birds model. It works fine when I was testing it with close pictures. But when I moved the pictures further away my camera, the model was not able to detect birds. My guess is in this line of code data = ImageDataBunch.from_folder(path=path_img, bs=48, valid_pct= 0.2, ds_tfms=get_transforms(), size=299, classes=[‘birds’, ‘others’]) After checked…

FastAi How to turn off crop in ImageDataBunch

I just trained my birds model. It works fine when I was testing it with close pictures. But when I moved the pictures further away my camera, the model was not able to detect birds. My guess is in this line of code data = ImageDataBunch.from_folder(path=path_img, bs=48, valid_pct= 0.2, ds_tfms=get_transforms(), size=299, classes=[‘birds’, ‘others’]) After checked…

FastAi How to turn off crop in ImageDataBunch

I just trained my birds model. It works fine when I was testing it with close pictures. But when I moved the pictures further away my camera, the model was not able to detect birds. My guess is in this line of code data = ImageDataBunch.from_folder(path=path_img, bs=48, valid_pct= 0.2, ds_tfms=get_transforms(), size=299, classes=[‘birds’, ‘others’]) After checked…

List of currently available Artificial General Intelligence (AGI)/strong AI systems

I wished to compile a (somewhat) comprehensive list of companies and organizations who are developing “Artificial General Intelligence (AGI)” or “strong AI” systems, their products and purported techniques and technologies they are using to create such systems. The definition of AGI that I’m referring to: The intelligence of a machine that can understand or learn…

not sure if fine-tuned network is finely-tuned

I am practicing with Resnet50 fine tuning for binary classification task, here is my code snippet. base_model = ResNet50(weights=’imagenet’, include_top=False) x = base_model.output x = keras.layers.GlobalAveragePooling2D(name=’avg_pool’)(x) x = Dropout(0.8)(x) model_prediction = keras.layers.Dense(1, activation=’sigmoid’, name=’predictions’)(x) model = keras.models.Model(inputs=base_model.input, outputs=model_prediction) opt = SGD(lr = 0.01, momentum = 0.9, nesterov = False) model.compile(loss=’binary_crossentropy’, optimizer=opt, metrics=[‘accuracy’]) # train_datagen =…

Can anyone explain the pixelwise accuracy metric used in this paper? Also a question to the KL Divergence Loss

So I am making a project based on this paper: https://arxiv.org/ftp/arxiv/papers/1901/1901.07761.pdf In this paper, a U-Net is used to generate optimized mechanical structures. I am trying to recreate the model and use it on my own generated data. Now I have two questions: In 7.1 a pixelwise accuracy is mentioned. Right now I am using…