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docs: 📝 supervision/dataset/core.py >>>/... removed

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Signed-off-by: Onuralp SEZER <thunderbirdtr@gmail.com>
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Onuralp SEZER committed 2024-01-24 13:01:55 +03:00
1 parent 2d1aa3b996
commit f03be21a9f
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+78 -81
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supervision/dataset/core.py
+78 -81
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@@ -118,13 +118,13 @@ class DetectionDataset(BaseDataset):
Example:
```python
>>> import supervision as sv
import supervision as sv
>>> ds = sv.DetectionDataset(...)
>>> train_ds, test_ds = ds.split(split_ratio=0.7,
... random_state=42, shuffle=True)
>>> len(train_ds), len(test_ds)
(700, 300)
ds = sv.DetectionDataset(...)
train_ds, test_ds = ds.split(split_ratio=0.7,
random_state=42, shuffle=True)
len(train_ds), len(test_ds)
# (700, 300)
```
"""
@@ -231,24 +231,24 @@ class DetectionDataset(BaseDataset):
Example:
```python
>>> import roboflow
>>> from roboflow import Roboflow
>>> import supervision as sv
import roboflow
from roboflow import Roboflow
import supervision as sv
>>> roboflow.login()
roboflow.login()
>>> rf = Roboflow()
rf = Roboflow()
>>> project = rf.workspace(WORKSPACE_ID).project(PROJECT_ID)
>>> dataset = project.version(PROJECT_VERSION).download("voc")
project = rf.workspace(WORKSPACE_ID).project(PROJECT_ID)
dataset = project.version(PROJECT_VERSION).download("voc")
>>> ds = sv.DetectionDataset.from_pascal_voc(
... images_directory_path=f"{dataset.location}/train/images",
... annotations_directory_path=f"{dataset.location}/train/labels"
... )
ds = sv.DetectionDataset.from_pascal_voc(
images_directory_path=f"{dataset.location}/train/images",
annotations_directory_path=f"{dataset.location}/train/labels"
)
>>> ds.classes
['dog', 'person']
ds.classes
# ['dog', 'person']
```
"""
@@ -288,25 +288,24 @@ class DetectionDataset(BaseDataset):
Example:
```python
>>> import roboflow
>>> from roboflow import Roboflow
>>> import supervision as sv
import roboflow
from roboflow import Roboflow
import supervision as sv
>>> roboflow.login()
roboflow.login()
rf = Roboflow()
>>> rf = Roboflow()
project = rf.workspace(WORKSPACE_ID).project(PROJECT_ID)
dataset = project.version(PROJECT_VERSION).download("yolov5")
>>> project = rf.workspace(WORKSPACE_ID).project(PROJECT_ID)
>>> dataset = project.version(PROJECT_VERSION).download("yolov5")
ds = sv.DetectionDataset.from_yolo(
images_directory_path=f"{dataset.location}/train/images",
annotations_directory_path=f"{dataset.location}/train/labels",
data_yaml_path=f"{dataset.location}/data.yaml"
)
>>> ds = sv.DetectionDataset.from_yolo(
... images_directory_path=f"{dataset.location}/train/images",
... annotations_directory_path=f"{dataset.location}/train/labels",
... data_yaml_path=f"{dataset.location}/data.yaml"
... )
>>> ds.classes
['dog', 'person']
ds.classes
# ['dog', 'person']
```
"""
classes, images, annotations = load_yolo_annotations(
@@ -394,24 +393,23 @@ class DetectionDataset(BaseDataset):
Example:
```python
>>> import roboflow
>>> from roboflow import Roboflow
>>> import supervision as sv
import roboflow
from roboflow import Roboflow
import supervision as sv
>>> roboflow.login()
roboflow.login()
rf = Roboflow()
>>> rf = Roboflow()
project = rf.workspace(WORKSPACE_ID).project(PROJECT_ID)
dataset = project.version(PROJECT_VERSION).download("coco")
>>> project = rf.workspace(WORKSPACE_ID).project(PROJECT_ID)
>>> dataset = project.version(PROJECT_VERSION).download("coco")
ds = sv.DetectionDataset.from_coco(
images_directory_path=f"{dataset.location}/train",
annotations_path=f"{dataset.location}/train/_annotations.coco.json",
)
>>> ds = sv.DetectionDataset.from_coco(
... images_directory_path=f"{dataset.location}/train",
... annotations_path=f"{dataset.location}/train/_annotations.coco.json",
... )
>>> ds.classes
['dog', 'person']
ds.classes
# ['dog', 'person']
```
"""
classes, images, annotations = load_coco_annotations(
@@ -486,25 +484,25 @@ class DetectionDataset(BaseDataset):
Example:
```python
>>> import supervision as sv
import supervision as sv
>>> ds_1 = sv.DetectionDataset(...)
>>> len(ds_1)
100
>>> ds_1.classes
['dog', 'person']
ds_1 = sv.DetectionDataset(...)
len(ds_1)
# 100
ds_1.classes
# ['dog', 'person']
>>> ds_2 = sv.DetectionDataset(...)
>>> len(ds_2)
200
>>> ds_2.classes
['cat']
ds_2 = sv.DetectionDataset(...)
len(ds_2)
# 200
ds_2.classes
# ['cat']
>>> ds_merged = sv.DetectionDataset.merge([ds_1, ds_2])
>>> len(ds_merged)
300
>>> ds_merged.classes
['cat', 'dog', 'person']
ds_merged = sv.DetectionDataset.merge([ds_1, ds_2])
len(ds_merged)
# 300
ds_merged.classes
# ['cat', 'dog', 'person']
```
"""
merged_images, merged_annotations = {}, {}
@@ -571,13 +569,13 @@ class ClassificationDataset(BaseDataset):
Example:
```python
>>> import supervision as sv
import supervision as sv
>>> cd = sv.ClassificationDataset(...)
>>> train_cd,test_cd = cd.split(split_ratio=0.7,
... random_state=42,shuffle=True)
>>> len(train_cd), len(test_cd)
(700, 300)
cd = sv.ClassificationDataset(...)
train_cd,test_cd = cd.split(split_ratio=0.7,
random_state=42,shuffle=True)
len(train_cd), len(test_cd)
# (700, 300)
```
"""
image_names = list(self.images.keys())
@@ -639,20 +637,19 @@ class ClassificationDataset(BaseDataset):
Example:
```python
>>> import roboflow
>>> from roboflow import Roboflow
>>> import supervision as sv
import roboflow
from roboflow import Roboflow
import supervision as sv
>>> roboflow.login()
roboflow.login()
rf = Roboflow()
>>> rf = Roboflow()
project = rf.workspace(WORKSPACE_ID).project(PROJECT_ID)
dataset = project.version(PROJECT_VERSION).download("folder")
>>> project = rf.workspace(WORKSPACE_ID).project(PROJECT_ID)
>>> dataset = project.version(PROJECT_VERSION).download("folder")
>>> cd = sv.ClassificationDataset.from_folder_structure(
... root_directory_path=f"{dataset.location}/train"
... )
cd = sv.ClassificationDataset.from_folder_structure(
root_directory_path=f"{dataset.location}/train"
)
```
"""
classes = os.listdir(root_directory_path)