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@@ -1,3 +1,73 @@
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# [NA-Birds](http://dl.allaboutbirds.org/nabirds) dataset wrapper
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-To see how to use this library take a look at [nabirds/display.py](nabirds/display.py).
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+For more deatils to see how to use this library take a look at [nabirds/display.py](nabirds/display.py).
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+
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+## Annotation and Image Loading
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+
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+Here is some example code how to load images and use the predefined train-test split.
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+
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+```python
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+# replace NAB_Annotations with CUB_Annotations to load CUB200-2011 annotations
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+from nabirds import NAB_Annotations, Dataset
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+
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+annot = NAB_Annotations("path/to/nab/folder")
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+
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+train_data = Dataset(annot.train_uuids, annot)
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+test_data = Dataset(annot.test_uuids, annot)
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+
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+print("Loaded {} training and {} test images".format(len(train_data), len(test_data)))
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+```
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+
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+## Dataset Iteration
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+```python
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+import matplotlib.pyplot as plt
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+
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+# either access the images directly
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+im, parts, label = test_data[100]
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+plt.imshow(im)
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+plt.show()
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+
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+# or iterate over the dataset
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+for im, parts, label in train_data:
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+ plt.imshow(im)
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+ plt.show()
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+
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+```
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+
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+## Working with Part Annotations
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+Both datasets (NAB and CUB) have part annotations. Each annotation has for each of the predefined parts the location of this part and a boolean (`0` or `1`) value whether this part is visible. A [`Dataset`](nabirds/dataset/__init__.py#L5) instance returns besides the image and the class label this information:
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+
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+```python
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+
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+im, parts, label = train_data[100]
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+
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+print(parts)
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+# array([[ 0, 529, 304, 1],
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+# [ 1, 427, 277, 1],
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+# [ 2, 368, 323, 1],
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+# [ 3, 0, 0, 0],
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+# [ 4, 449, 292, 1],
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+# [ 5, 398, 502, 1],
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+# [ 6, 430, 398, 1],
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+# [ 7, 0, 0, 0],
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+# [ 8, 365, 751, 1],
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+# [ 9, 0, 0, 0],
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+# [ 10, 0, 0, 0]])
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+
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+```
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+
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+In order to filter by only visible parts use the [`utils.visible_part_locs`](nabirds/dataset/utils.py#L28) function. It returns the indices and the x-y positions of the visible parts:
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+
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+```python
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+idxs, xy = visible_part_locs(parts)
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+print(idxs)
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+# array([0, 1, 2, 4, 5, 6, 8])
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+print(xy)
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+# array([[529, 427, 368, 449, 398, 430, 365],
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+# [304, 277, 323, 292, 502, 398, 751]])
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+
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+x, y = xy
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+plt.imshow(im)
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+plt.scatter(x,y, marker="x", c=idxs)
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+plt.show()
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+```
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