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

Signed-off-by: Mohammed Yasin <32206511+Y-T-G@users.noreply.github.com>

docs/en/tasks/detect.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"

docs/en/tasks/obb.md

@@ -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"

docs/en/tasks/pose.md

@@ -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"

docs/en/tasks/segment.md

@@ -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"