Comments (2)
👋 Hello @lyndalaghmardi, thank you for your interest in Ultralytics YOLOv8 🚀! We recommend a visit to the Docs for new users where you can find many Python and CLI usage examples and where many of the most common questions may already be answered.
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Install
Pip install the ultralytics
package including all requirements in a Python>=3.8 environment with PyTorch>=1.8.
pip install ultralytics
Environments
YOLOv8 may be run in any of the following up-to-date verified environments (with all dependencies including CUDA/CUDNN, Python and PyTorch preinstalled):
- Notebooks with free GPU:
- Google Cloud Deep Learning VM. See GCP Quickstart Guide
- Amazon Deep Learning AMI. See AWS Quickstart Guide
- Docker Image. See Docker Quickstart Guide
Status
If this badge is green, all Ultralytics CI tests are currently passing. CI tests verify correct operation of all YOLOv8 Modes and Tasks on macOS, Windows, and Ubuntu every 24 hours and on every commit.
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@lyndalaghmardi hello! It looks like you've made great progress with your project. For cropping the blue flowers based on the bounding box and tracker ID, your approach seems mostly correct. However, the error might be occurring from how you're accessing the bounding box from your detections
object.
Make sure that detections.bbox
and detections.tracker_id
are indexed properly and that flower_id
corresponds to a valid tracker ID. Here's a slight modification to your code:
if flower_color == "blue":
# Get tracked flower's index
index = (detections.tracker_id == flower_id).nonzero()[0]
if index:
bbox = detections.bbox[index][0]
# Crop the flower from the frame
cropped_flower = frame[int(bbox[1]):int(bbox[3]), int(bbox[0]):int(bbox[2])]
Make sure your flower_id
matches the tracked IDs, and confirm your bounding box coordinates are integers before slicing the frame array. If you continue to experience issues, please share the exact error message, which will help in diagnosing the problem more precisely. Happy coding! 🌼
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Related Issues (20)
- Why some of the objects in pose estimation are not getting detected? HOT 1
- What file is required for classification classes weights? HOT 5
- Corrupt JPEG data: 1199 extraneous bytes before marker 0xd4 HOT 3
- The accuracy of yolov8l-obb only reached 55+, which is significantly lower than the 80.7 mentioned in the official documentation. HOT 3
- RGB images to HSV space HOT 1
- Correlation between weight file size and number of parameters HOT 2
- Need Help to Repeat YOLOv8n HOT 4
- RuntimeError: invalid shape when training YOLOWorld on MixedGrounding Dataset HOT 8
- How do I manually set the anchor for yolov5 HOT 3
- Detection for Small objects HOT 4
- Illegal instruction: 4 with yolov8 pose task testing HOT 6
- coco format HOT 10
- training yolov8 on a different data set than I had previously trained it on became extremely slow HOT 2
- code issue HOT 2
- guides/object-counting/ HOT 2
- how to add Transformer block to YOLOv8-seg architecture? HOT 3
- Error Dimension mismatch while using model.track (object-counting) on Coral Edge TPU HOT 10
- Triton remote model not working with https HOT 1
- Detection model training with segmentation annotation HOT 3
- YOLOv10 branch doesn't exist in newer ultralytics versions HOT 4
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