Add distance calculation feature in vision-eye (#8616)

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: Muhammad Rizwan Munawar <chr043416@gmail.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>

docs/en/guides/vision-eye.md

@@ -12,10 +12,10 @@ keywords: Ultralytics, YOLOv8, Object Detection, Object Tracking, IDetection, Vi
 
 ## Samples
 
-|                                                                        VisionEye View                                                                        |                                                                        VisionEye View With Object Tracking                                                                        |
-|:------------------------------------------------------------------------------------------------------------------------------------------------------------:|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|
-| ![VisionEye View Object Mapping using Ultralytics YOLOv8](https://github.com/RizwanMunawar/ultralytics/assets/62513924/7d593acc-2e37-41b0-ad0e-92b4ffae6647) | ![VisionEye View Object Mapping with Object Tracking using Ultralytics YOLOv8](https://github.com/RizwanMunawar/ultralytics/assets/62513924/fcd85952-390f-451e-8fb0-b82e943af89c) |
-|                                                    VisionEye View Object Mapping using Ultralytics YOLOv8                                                    |                                                    VisionEye View Object Mapping with Object Tracking using Ultralytics YOLOv8                                                    |
+|                                                                        VisionEye View                                                                        |                                                                        VisionEye View With Object Tracking                                                                        |                                                                 VisionEye View With Distance Calculation                                                                  |
+|:------------------------------------------------------------------------------------------------------------------------------------------------------------:|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|
+| ![VisionEye View Object Mapping using Ultralytics YOLOv8](https://github.com/RizwanMunawar/ultralytics/assets/62513924/7d593acc-2e37-41b0-ad0e-92b4ffae6647) | ![VisionEye View Object Mapping with Object Tracking using Ultralytics YOLOv8](https://github.com/RizwanMunawar/ultralytics/assets/62513924/fcd85952-390f-451e-8fb0-b82e943af89c) | ![VisionEye View with Distance Calculation using Ultralytics YOLOv8](https://github.com/RizwanMunawar/RizwanMunawar/assets/62513924/18c4dafe-a22e-4fa9-a7d4-2bb293562a95) |
+|                                                    VisionEye View Object Mapping using Ultralytics YOLOv8                                                    |                                                    VisionEye View Object Mapping with Object Tracking using Ultralytics YOLOv8                                                    |                                                     VisionEye View with Distance Calculation using Ultralytics YOLOv8                                                     |
 
 !!! Example "VisionEye Object Mapping using YOLOv8"
 
@@ -105,6 +105,63 @@ keywords: Ultralytics, YOLOv8, Object Detection, Object Tracking, IDetection, Vi
         cap.release()
         cv2.destroyAllWindows()
         ```
+    
+    === "VisionEye with Distance Calculation"
+    
+        ```python
+        import cv2
+        import math
+        from ultralytics import YOLO
+        from ultralytics.utils.plotting import Annotator, colors
+        
+        model = YOLO("yolov8s.pt")
+        cap = cv2.VideoCapture("Path/to/video/file.mp4")
+        
+        w, h, fps = (int(cap.get(x)) for x in (cv2.CAP_PROP_FRAME_WIDTH, cv2.CAP_PROP_FRAME_HEIGHT, cv2.CAP_PROP_FPS))
+        
+        out = cv2.VideoWriter('visioneye-distance-calculation.avi', cv2.VideoWriter_fourcc(*'MJPG'), fps, (w, h))
+        
+        center_point = (0, h)
+        pixel_per_meter = 10
+        
+        txt_color, txt_background, bbox_clr = ((0, 0, 0), (255, 255, 255), (255, 0, 255))
+        
+        while True:
+            ret, im0 = cap.read()
+            if not ret:
+                print("Video frame is empty or video processing has been successfully completed.")
+                break
+        
+            annotator = Annotator(im0, line_width=2)
+        
+            results = model.track(im0, persist=True)
+            boxes = results[0].boxes.xyxy.cpu()
+        
+            if results[0].boxes.id is not None:
+                track_ids = results[0].boxes.id.int().cpu().tolist()
+        
+                for box, track_id in zip(boxes, track_ids):
+                    annotator.box_label(box, label=str(track_id), color=bbox_clr)
+                    annotator.visioneye(box, center_point)
+        
+                    x1, y1 = int((box[0] + box[2]) // 2), int((box[1] + box[3]) // 2)    # Bounding box centroid
+        
+                    distance = (math.sqrt((x1 - center_point[0]) ** 2 + (y1 - center_point[1]) ** 2))/pixel_per_meter
+        
+                    text_size, _ = cv2.getTextSize(f"Distance: {distance:.2f} m", cv2.FONT_HERSHEY_SIMPLEX,1.2, 3)
+                    cv2.rectangle(im0, (x1, y1 - text_size[1] - 10),(x1 + text_size[0] + 10, y1), txt_background, -1)
+                    cv2.putText(im0, f"Distance: {distance:.2f} m",(x1, y1 - 5), cv2.FONT_HERSHEY_SIMPLEX, 1.2,txt_color, 3)
+        
+            out.write(im0)
+            cv2.imshow("visioneye-distance-calculation", im0)
+        
+            if cv2.waitKey(1) & 0xFF == ord('q'):
+                break
+        
+        out.release()
+        cap.release()
+        cv2.destroyAllWindows()
+        ```
 
 ### `visioneye` Arguments
 

docs/en/reference/models/yolo/model.md

@@ -14,3 +14,7 @@ keywords: Ultralytics YOLO, YOLO, YOLO model, Model Training, Machine Learning,
 ## ::: ultralytics.models.yolo.model.YOLO
 
 <br><br>
+
+## ::: ultralytics.models.yolo.model.YOLOWorld
+
+<br><br>

docs/en/reference/nn/modules/block.md

@@ -86,3 +86,23 @@ keywords: YOLO, Ultralytics, neural network, nn.modules.block, Proto, HGBlock, S
 ## ::: ultralytics.nn.modules.block.ResNetLayer
 
 <br><br>
+
+## ::: ultralytics.nn.modules.block.MaxSigmoidAttnBlock
+
+<br><br>
+
+## ::: ultralytics.nn.modules.block.C2fAttn
+
+<br><br>
+
+## ::: ultralytics.nn.modules.block.ImagePoolingAttn
+
+<br><br>
+
+## ::: ultralytics.nn.modules.block.ContrastiveHead
+
+<br><br>
+
+## ::: ultralytics.nn.modules.block.BNContrastiveHead
+
+<br><br>

docs/en/reference/nn/modules/head.md

@@ -31,6 +31,10 @@ keywords: Ultralytics, YOLO, Detection, Pose, RTDETRDecoder, nn modules, guides
 
 <br><br>
 
+## ::: ultralytics.nn.modules.head.WorldDetect
+
+<br><br>
+
 ## ::: ultralytics.nn.modules.head.RTDETRDecoder
 
 <br><br>

docs/en/reference/nn/tasks.md

@@ -39,6 +39,10 @@ keywords: Ultralytics, YOLO, nn tasks, DetectionModel, PoseModel, RTDETRDetectio
 
 <br><br>
 
+## ::: ultralytics.nn.tasks.WorldModel
+
+<br><br>
+
 ## ::: ultralytics.nn.tasks.Ensemble
 
 <br><br>

ultralytics/engine/exporter.py

@@ -107,7 +107,7 @@ def export_formats():
         ["TensorFlow Edge TPU", "edgetpu", "_edgetpu.tflite", True, False],
         ["TensorFlow.js", "tfjs", "_web_model", True, False],
         ["PaddlePaddle", "paddle", "_paddle_model", True, True],
-        ["ncnn", "ncnn", "_ncnn_model", True, True],
+        ["NCNN", "ncnn", "_ncnn_model", True, True],
     ]
     return pandas.DataFrame(x, columns=["Format", "Argument", "Suffix", "CPU", "GPU"])