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This dataset contains several microstructure treatments:
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1. [`variable_radius.zip`](https://huggingface.co/datasets/cmudrc/porous-microstructure-strain-fields/blob/main/variable_radius.zip) - Ten microstructures with defects of variable radii, from 0.01 mm to 0.5 mm. To load it, run: ```datasets.load_dataset(data_files=['variable_radius.zip'])```
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2. [`variable_number.zip`](https://huggingface.co/datasets/cmudrc/porous-microstructure-strain-fields/blob/main/variable_number.zip) - Ten microstructures with different numbers of defects, from 20 to 200. To load it, run: ```datasets.load_dataset(data_files=['variable_number.zip'])```
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3. [`circular_defects.zip`](https://huggingface.co/datasets/cmudrc/porous-microstructure-strain-fields/blob/main/circular_defects.zip) - This data contains image data of 1000 samples of microstructures with 100 circular porosity defects having their radii uniformly distributed in the range 0.1 – 0.5 mm, and their corresponding strain fields. To load it, run: ```datasets.load_dataset(data_files=['circular_defects.zip'])```
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This dataset contains several microstructure treatments:
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1. [`variable_radius.zip`](https://huggingface.co/datasets/cmudrc/porous-microstructure-strain-fields/blob/main/variable_radius.zip) - Ten microstructures with defects of variable radii, from 0.01 mm to 0.5 mm. To load it, run: ```datasets.load_dataset(data_files=['variable_radius.zip'])```
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2. [`variable_number.zip`](https://huggingface.co/datasets/cmudrc/porous-microstructure-strain-fields/blob/main/variable_number.zip) - Ten microstructures with different numbers of defects, from 20 to 200. To load it, run: ```datasets.load_dataset(data_files=['variable_number.zip'])```
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3. [`circular_defects.zip`](https://huggingface.co/datasets/cmudrc/porous-microstructure-strain-fields/blob/main/circular_defects.zip) - This data contains image data of 1000 samples of microstructures with 100 circular porosity defects having their radii uniformly distributed in the range 0.1 – 0.5 mm, and their corresponding strain fields. To load it, run: ```datasets.load_dataset(data_files=['circular_defects.zip'])```
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4. A variety of different defect shapes in smaller datasets, with train/test splites (500 samples and 50 samples, respectively).
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1. Circles
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2. Crescents
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3. Ellipses
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4. Peanuts
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5. Rectangles
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6. Triangles
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