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37 | 37 | "* Data pre-processing functions, as typically pathology data is given as a whole slide, which cannot be directly used for training as it's too large in size, in particular check `consep_nuclei_dataset`\n", |
38 | 38 | "* Uses the dataset: \n", |
39 | 39 | "\n", |
40 | | - "This model is trained using [DenseNet121](https://docs.monai.io/en/latest/networks.html#densenet121) over [ConSeP](https://warwick.ac.uk/fac/cross_fac/tia/data/hovernet) dataset. \n", |
| 40 | + "This model is trained using [DenseNet121](https://docs.monai.io/en/latest/networks.html#densenet121) over [CoNSeP](https://warwick.ac.uk/fac/cross_fac/tia/data/hovernet) dataset. \n", |
41 | 41 | "\n", |
42 | 42 | "> Please note that this model uses existing label mask as additional signal input while training.\n", |
43 | 43 | "\n", |
|
92 | 92 | "import torch.distributed\n", |
93 | 93 | "from IPython.display import Image as IImage\n", |
94 | 94 | "from monai.apps.nuclick.transforms import AddLabelAsGuidanced, SetLabelClassd, SplitLabeld\n", |
95 | | - "from monai.apps.utils import download_and_extract\n", |
96 | 95 | "from monai.config import IgniteInfo, print_config\n", |
97 | 96 | "from monai.data import CacheDataset, DataLoader\n", |
98 | 97 | "from monai.engines import SupervisedEvaluator, SupervisedTrainer\n", |
|
146 | 145 | "cell_type": "markdown", |
147 | 146 | "metadata": {}, |
148 | 147 | "source": [ |
149 | | - "## Configure Workspace Path" |
150 | | - ] |
151 | | - }, |
152 | | - { |
153 | | - "cell_type": "code", |
154 | | - "execution_count": 4, |
155 | | - "metadata": {}, |
156 | | - "outputs": [ |
157 | | - { |
158 | | - "name": "stderr", |
159 | | - "output_type": "stream", |
160 | | - "text": [ |
161 | | - "consep_dataset.zip: 146MB [00:23, 6.41MB/s] " |
162 | | - ] |
163 | | - }, |
164 | | - { |
165 | | - "name": "stdout", |
166 | | - "output_type": "stream", |
167 | | - "text": [ |
168 | | - "2022-12-06 10:46:41,905 - INFO - Downloaded: /tmp/tmp834vb_2l/consep_dataset.zip\n", |
169 | | - "2022-12-06 10:46:41,907 - INFO - Expected md5 is None, skip md5 check for file /tmp/tmp834vb_2l/consep_dataset.zip.\n", |
170 | | - "2022-12-06 10:46:41,910 - INFO - Writing into directory: workspace.\n" |
171 | | - ] |
172 | | - }, |
173 | | - { |
174 | | - "name": "stderr", |
175 | | - "output_type": "stream", |
176 | | - "text": [ |
177 | | - "\n" |
178 | | - ] |
179 | | - } |
180 | | - ], |
181 | | - "source": [ |
182 | | - "consep_zip = \"https://warwick.ac.uk/fac/cross_fac/tia/data/hovernet/consep_dataset.zip\"\n", |
183 | | - "consep_dir = os.path.join(workspace_path, \"CoNSeP\")\n", |
184 | | - "\n", |
185 | | - "if not os.path.exists(consep_dir):\n", |
186 | | - " download_and_extract(consep_zip, output_dir=workspace_path)" |
| 148 | + "## Configure Workspace Path\n", |
| 149 | + "The datasets used in the examples are from [CoNSeP](https://warwick.ac.uk/fac/cross_fac/tia/data/HoVerNet/). Each user is responsible for checking the content of datasets and the applicable licenses and determining if suitable for the intended use." |
187 | 150 | ] |
188 | 151 | }, |
189 | 152 | { |
|
204 | 167 | } |
205 | 168 | ], |
206 | 169 | "source": [ |
| 170 | + "# consep_dir points to the root directory of the consep dataset\n", |
| 171 | + "consep_dir = os.path.join(workspace_path, \"CoNSeP\")\n", |
| 172 | + "\n", |
207 | 173 | "IImage(filename=os.path.join(consep_dir, \"Train\", \"Overlay\", \"train_8.png\"))" |
208 | 174 | ] |
209 | 175 | }, |
|
213 | 179 | "source": [ |
214 | 180 | "## Pre-processing utility functions\n", |
215 | 181 | "\n", |
216 | | - "`consep_nuclei_dataset` reads the raw Image and Matlab files provided in ConSeP dataset. For each Nuclei it tries to create a patch of 128x128 with single nuclei labeled with correspnding class index and rest of the nuclei falling in this patch are labeled as others (mask_value: 255)\n", |
| 182 | + "The `consep_nuclei_dataset` function processes the raw image and Matlab files from the CoNSeP dataset. For each nucleus, it generates a 128x128 patch wherein the target nucleus is labeled with its corresponding class index, and all other nuclei within the patch are labeled as 'others' (using a mask value of 255).\n", |
217 | 183 | "\n" |
218 | 184 | ] |
219 | 185 | }, |
|
225 | 191 | "source": [ |
226 | 192 | "def consep_nuclei_dataset(datalist, output_dir, crop_size, min_area=80, min_distance=20, limit=0) -> List[Dict]:\n", |
227 | 193 | " \"\"\"\n", |
228 | | - " Utility to pre-process and create dataset list for Patches per Nuclei for training over ConSeP dataset.\n", |
| 194 | + " Utility to pre-process and create a dataset list for Patches per Nuclei for training over CoNSeP dataset.\n", |
229 | 195 | "\n", |
230 | 196 | " Args:\n", |
231 | 197 | " datalist: A list of data dictionary. Each entry should at least contain 'image_key': <image filename>.\n", |
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