targetran - npm Package Compare versions

Comparing version 0.10.4 to 0.11.7

PKG-INFO

 Metadata-Version: 2.1
 Name: targetran
-Version: 0.10.4
+Version: 0.11.7
 Summary: Target transformation for data augmentation in objection detection
@@ -11,3 +11,3 @@ Home-page: https://github.com/bhky/targetran
 Classifier: Operating System :: OS Independent
-Requires-Python: >=3.7
+Requires-Python: >=3.8
 Description-Content-Type: text/markdown
@@ -352,3 +352,4 @@ License-File: LICENSE
     .map(image_only(affine_transform)) \
-    .map(image_only(TFResize((256, 256))))
+    .map(image_only(TFResize((256, 256)))) \
+    .batch(32)  # Conventional batching can be used for classification setup.
 ```
@@ -363,2 +364,3 @@ ```python
 ds = PTDataset(..., transforms=transforms)
+data_loader = DataLoader(ds, batch_size=32)
 ```
@@ -365,0 +367,0 @@

README.md

@@ -337,3 +337,4 @@ ![logo](logo/targetran_logo.png)
     .map(image_only(affine_transform)) \
-    .map(image_only(TFResize((256, 256))))
+    .map(image_only(TFResize((256, 256)))) \
+    .batch(32)  # Conventional batching can be used for classification setup.
 ```
@@ -348,2 +349,3 @@ ```python
 ds = PTDataset(..., transforms=transforms)
+data_loader = DataLoader(ds, batch_size=32)
 ```
@@ -350,0 +352,0 @@

setup.cfg

@@ -17,6 +17,6 @@ [metadata]
 packages = find:
-python_requires = >=3.7
+python_requires = >=3.8
 install_requires = 
 	opencv-python
-	numpy>=1.21.0
+	numpy>=1.22.0
 
@@ -23,0 +23,0 @@ [options.package_data]

targetran.egg-info/PKG-INFO

 Metadata-Version: 2.1
 Name: targetran
-Version: 0.10.4
+Version: 0.11.7
 Summary: Target transformation for data augmentation in objection detection
@@ -11,3 +11,3 @@ Home-page: https://github.com/bhky/targetran
 Classifier: Operating System :: OS Independent
-Requires-Python: >=3.7
+Requires-Python: >=3.8
 Description-Content-Type: text/markdown
@@ -352,3 +352,4 @@ License-File: LICENSE
     .map(image_only(affine_transform)) \
-    .map(image_only(TFResize((256, 256))))
+    .map(image_only(TFResize((256, 256)))) \
+    .batch(32)  # Conventional batching can be used for classification setup.
 ```
@@ -363,2 +364,3 @@ ```python
 ds = PTDataset(..., transforms=transforms)
+data_loader = DataLoader(ds, batch_size=32)
 ```
@@ -365,0 +367,0 @@

targetran.egg-info/requires.txt

 opencv-python
-numpy>=1.21.0
+numpy>=1.22.0

targetran/__init__.py

@@ -1,3 +0,3 @@
-__version__ = "0.10.4"
+__version__ = "0.11.7"
 __author__ = "Bosco Yung"
 __license__ = "MIT"

targetran/_np_functional.py

@@ -25,3 +25,3 @@ """
 def _np_range(start: int, end: int, step: int) -> NDIntArray:
-    return np.arange(start, end, step, dtype=np.int32)  # type: ignore
+    return np.arange(start, end, step, dtype=np.int32)
 
@@ -34,7 +34,7 @@
 def _np_round_to_int(x: NDAnyArray) -> NDIntArray:
-    return np.rint(x.astype(dtype=np.float32)).astype(dtype=np.int32)  # type: ignore
+    return np.rint(x.astype(dtype=np.float32)).astype(dtype=np.int32)
 
 
 def _np_logical_and(x: NDBoolArray, y: NDBoolArray) -> NDBoolArray:
-    return np.logical_and(x, y)  # type: ignore
+    return np.logical_and(x, y)
 
@@ -54,3 +54,3 @@
     )
-    return np.pad(image, pad_width=pad_width, constant_values=0)  # type: ignore
+    return np.pad(image, pad_width=pad_width, constant_values=0)
 
@@ -57,0 +57,0 @@

targetran/np/_np.py

@@ -52,3 +52,3 @@ """
         _np_pad_image, _np_range, _np_cast_to_int, _np_round_to_int, np.repeat,
-        np.tile,
+        np.tile,  # type: ignore
         np.ones_like, np.stack, np.concatenate, np.matmul,
@@ -264,3 +264,3 @@ np.clip, np.floor, np.ceil, _np_gather_image,
         self._interpolation = interpolation
-        self._identity_mat = np.expand_dims(np.array([  # type: ignore
+        self._identity_mat = np.expand_dims(np.array([
             [1.0, 0.0, 0.0], [0.0, 1.0, 0.0], [0.0, 0.0, 1.0]
@@ -289,6 +289,6 @@ ]), axis=0)
             conditions = np.reshape(rand_fn() < probs, (len(probs), 1, 1))
-            image_dest_tran_mats = np.where(
+            image_dest_tran_mats = np.where(  # type: ignore
                 conditions, image_dest_tran_mats, self._identity_mat
             )
-            bboxes_tran_mats = np.where(
+            bboxes_tran_mats = np.where(  # type: ignore
                 conditions, bboxes_tran_mats, self._identity_mat
@@ -295,0 +295,0 @@ )

targetran/tf/_tf.py

@@ -254,3 +254,3 @@ """
         self._rng = tf.random.Generator.from_seed(
-            seed if seed is not None else np.random.randint(1e6)
+            seed if seed is not None else np.random.randint(1e6)  # type: ignore
         )
@@ -257,0 +257,0 @@ self.name = name

Alert delta unavailable

Currently unable to show alert delta for PyPI packages.

Improved metrics

Total package byte prevSize

113352

0.32%