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Add Discourse at https://community.ultralytics.com #59

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merged 4 commits into from
Jul 5, 2024
Merged

Add Discourse at https://community.ultralytics.com #59

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2edd803
Refactor code for speed and clarity
glenn-jocher Jul 5, 2024
bdc46c5
Auto-format by https://ultralytics.com/actions
UltralyticsAssistant Jul 5, 2024
142b625
Update utils.py
glenn-jocher Jul 5, 2024
2110d64
Auto-format by https://ultralytics.com/actions
UltralyticsAssistant Jul 5, 2024
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2 changes: 1 addition & 1 deletion README.md
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Expand Up @@ -5,7 +5,7 @@

Welcome to the [Ultralytics xView YOLOv3](https://github.com/ultralytics/xview-yolov3) repository! Here we provide code to train the powerful YOLOv3 object detection model on the xView dataset for the [xView Challenge](https://challenge.xviewdataset.org/). This challenge focuses on detecting objects from satellite imagery, advancing the state of the art in computer vision applications for remote sensing.

[![Ultralytics Actions](https://github.com/ultralytics/xview-yolov3/actions/workflows/format.yml/badge.svg)](https://github.com/ultralytics/xview-yolov3/actions/workflows/format.yml) <a href="https://ultralytics.com/discord"><img alt="Discord" src="https://img.shields.io/discord/1089800235347353640?logo=discord&logoColor=white&label=Discord&color=blue"></a>
[![Ultralytics Actions](https://github.com/ultralytics/xview-yolov3/actions/workflows/format.yml/badge.svg)](https://github.com/ultralytics/xview-yolov3/actions/workflows/format.yml) <a href="https://ultralytics.com/discord"><img alt="Discord" src="https://img.shields.io/discord/1089800235347353640?logo=discord&logoColor=white&label=Discord&color=blue"></a> <a href="https://community.ultralytics.com"><img alt="Ultralytics Forums" src="https://img.shields.io/discourse/users?server=https%3A%2F%2Fcommunity.ultralytics.com&logo=discourse&label=Forums&color=blue"></a>

<img src="https://github-production-user-asset-6210df.s3.amazonaws.com/26833433/238799379-bb3b02f0-dee4-4e67-80ae-4b2378b813ad.jpg?raw=true" width="100%">

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3 changes: 3 additions & 0 deletions utils/datasets.py
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Expand Up @@ -301,6 +301,9 @@ def resize_square(img, height=416, color=(0, 0, 0)): # resizes a rectangular im
def random_affine(
img, targets=None, degrees=(-10, 10), translate=(0.1, 0.1), scale=(0.9, 1.1), shear=(-3, 3), borderValue=(0, 0, 0)
):
"""Performs random affine transformations on an image and its target annotations, including rotation, translation,
scaling, and shearing.
"""
# torchvision.transforms.RandomAffine(degrees=(-10, 10), translate=(.1, .1), scale=(.9, 1.1), shear=(-10, 10))
# https://medium.com/uruvideo/dataset-augmentation-with-random-homographies-a8f4b44830d4
border = 750
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10 changes: 2 additions & 8 deletions utils/utils.py
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Expand Up @@ -517,15 +517,9 @@ def build_targets(pred_boxes, pred_conf, pred_cls, target, anchor_wh, nA, nC, nG


def non_max_suppression(prediction, conf_thres=0.5, nms_thres=0.4, mat=None, img=None, model2=None, device="cpu"):
prediction = prediction.cpu()
"""
Removes detections with lower object confidence score than 'conf_thres' and performs Non-Maximum Suppression to
further filter detections.

Returns detections with shape:
(x1, y1, x2, y2, object_conf, class_score, class_pred)
"""
"""Performs Non-Maximum Suppression on detection results, filtering out low-confidence detections."""

prediction = prediction.cpu()
output = [None for _ in range(len(prediction))]
# Gather bbox priors
srl = 6 # sigma rejection level
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