Add examples showing how to use `result` for all tasks (#19282)

Signed-off-by: Mohammed Yasin <32206511+Y-T-G@users.noreply.github.com>
pull/19267/head
Mohammed Yasin 4 weeks ago committed by GitHub
parent 384ace4617
commit aa1c6c9a24
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  1. 9
      docs/en/tasks/detect.md
  2. 7
      docs/en/tasks/obb.md
  3. 6
      docs/en/tasks/pose.md
  4. 6
      docs/en/tasks/segment.md

@ -122,6 +122,15 @@ Use a trained YOLO11n model to run predictions on images.
# Predict with the model
results = model("https://ultralytics.com/images/bus.jpg") # predict on an image
# Access the results
for result in results:
xywh = result.boxes.xywh # center-x, center-y, width, height
xywhn = result.boxes.xywhn # normalized
xyxy = result.boxes.xyxy # top-left-x, top-left-y, bottom-right-x, bottom-right-y
xyxyn = result.boxes.xyxyn # normalized
names = [result.names[cls.item()] for cls in result.boxes.cls.int()] # class name of each box
confs = result.boxes.conf # confidence score of each box
```
=== "CLI"

@ -142,6 +142,13 @@ Use a trained YOLO11n-obb model to run predictions on images.
# Predict with the model
results = model("https://ultralytics.com/images/boats.jpg") # predict on an image
# Access the results
for result in results:
xywhr = result.keypoints.xy # center-x, center-y, width, height, angle (radians)
xyxyxyxy = result.obb.xyxyxyxy # polygon format with 4-points
names = [result.names[cls.item()] for cls in result.obb.cls.int()] # class name of each box
confs = result.obb.conf # confidence score of each box
```
=== "CLI"

@ -143,6 +143,12 @@ Use a trained YOLO11n-pose model to run predictions on images.
# Predict with the model
results = model("https://ultralytics.com/images/bus.jpg") # predict on an image
# Access the results
for result in results:
xy = result.keypoints.xy # x and y coordinates
xyn = result.keypoints.xyn # normalized
kpts = result.keypoints.data # x, y, visibility (if available)
```
=== "CLI"

@ -127,6 +127,12 @@ Use a trained YOLO11n-seg model to run predictions on images.
# Predict with the model
results = model("https://ultralytics.com/images/bus.jpg") # predict on an image
# Access the results
for result in results:
xy = result.masks.xy # mask in polygon format
xyn = result.masks.xyn # normalized
masks = result.masks.data # mask in matrix format (num_objects x H x W)
```
=== "CLI"

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