utils-contrails-loss-functions.ipynb

{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"name":"python","version":"3.10.12","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"code","source":"# %% [markdown]\n# # Loss Functions for Contrail Detection\n\n# %% [code]\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\n# %% [markdown]\n# ## Dice Loss\n\n# %% [code]\nclass DiceLoss(nn.Module):\n    def __init__(self, weight=None, size_average=True):\n        super(DiceLoss, self).__init__()\n\n    def forward(self, inputs, targets, smooth=1):\n        \n        #comment out if your model contains a sigmoid or equivalent activation layer\n        inputs = F.sigmoid(inputs)       \n        \n        #flatten label and prediction tensors\n        inputs = inputs.view(-1)\n        targets = targets.view(-1)\n        \n        intersection = (inputs * targets).sum()                            \n        dice = (2.*intersection + smooth)/(inputs.sum() + targets.sum() + smooth)  \n        \n        return 1 - dice\n\n# %% [markdown]\n# ## Focal Loss\n\n# %% [code]\nclass FocalLoss(nn.Module):\n    def __init__(self, alpha=0.25, gamma=2, logits=False, reduce=True):\n        super(FocalLoss, self).__init__()\n        self.alpha = alpha\n        self.gamma = gamma\n        self.logits = logits\n        self.reduce = reduce\n\n    def forward(self, inputs, targets):\n        if self.logits:\n            BCE_loss = F.binary_cross_entropy_with_logits(inputs, targets, reduce=False)\n        else:\n            BCE_loss = F.binary_cross_entropy(inputs, targets, reduce=False)\n        pt = torch.exp(-BCE_loss)\n        F_loss = self.alpha * (1-pt)**self.gamma * BCE_loss\n\n        if self.reduce:\n            return torch.mean(F_loss)\n        else:\n            return F_loss","metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","execution":{"iopub.status.busy":"2023-08-06T06:43:16.774736Z","iopub.execute_input":"2023-08-06T06:43:16.775553Z","iopub.status.idle":"2023-08-06T06:43:20.988013Z","shell.execute_reply.started":"2023-08-06T06:43:16.775513Z","shell.execute_reply":"2023-08-06T06:43:20.986704Z"},"trusted":true},"execution_count":1,"outputs":[]}]}