targetran
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| Metadata-Version: 2.1 | ||
| Name: targetran | ||
| Version: 0.11.8 | ||
| Version: 0.11.9 | ||
| Summary: Target transformation for data augmentation in objection detection | ||
@@ -5,0 +5,0 @@ Home-page: https://github.com/bhky/targetran |
| Metadata-Version: 2.1 | ||
| Name: targetran | ||
| Version: 0.11.8 | ||
| Version: 0.11.9 | ||
| Summary: Target transformation for data augmentation in objection detection | ||
@@ -5,0 +5,0 @@ Home-page: https://github.com/bhky/targetran |
@@ -1,3 +0,3 @@ | ||
| __version__ = "0.11.8" | ||
| __version__ = "0.11.9" | ||
| __author__ = "Bosco Yung" | ||
| __license__ = "MIT" |
@@ -55,2 +55,3 @@ """ | ||
| ceil_fn: Callable[[T], T] | ||
| transpose_fn: Callable[[T], T] | ||
| gather_image_fn: Callable[[T, T], T] | ||
@@ -156,4 +157,5 @@ copy_fn: Callable[[T], T] | ||
| dists: T = image_orig_idxes - d.convert_fn(floor_floor_idxes) | ||
| # Reshape needed for broadcasting in the gather step. | ||
| floor_weights = d.reshape_fn(1.0 - dists, (-1, 2)) | ||
| # Transpose to shape (-1, 2), needed for broadcasting in the later | ||
| # gather-values step. See the return shape of gather_image_fn. | ||
| floor_weights = d.transpose_fn(1.0 - dists) | ||
| ceil_weights: T = 1.0 - floor_weights | ||
@@ -160,0 +162,0 @@ floor_floor_weights = floor_weights[:, :1] * floor_weights[:, 1:] |
@@ -54,3 +54,3 @@ """ | ||
| np.ones_like, np.stack, np.concatenate, np.matmul, | ||
| np.clip, np.floor, np.ceil, _np_gather_image, | ||
| np.clip, np.floor, np.ceil, np.transpose, _np_gather_image, | ||
| np.copy, np.max, np.min, | ||
@@ -57,0 +57,0 @@ _np_logical_and, _np_boolean_mask |
@@ -104,4 +104,4 @@ """ | ||
| tf.repeat, tf.tile, tf.ones_like, tf.stack, tf.concat, tf.matmul, | ||
| tf.clip_by_value, tf.math.floor, tf.math.ceil, _tf_gather_image, | ||
| tf.identity, tf.reduce_max, tf.reduce_min, | ||
| tf.clip_by_value, tf.math.floor, tf.math.ceil, tf.transpose, | ||
| _tf_gather_image, tf.identity, tf.reduce_max, tf.reduce_min, | ||
| tf.logical_and, tf.boolean_mask | ||
@@ -108,0 +108,0 @@ ) |
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