Traffic Light Detection & Line Lane & Drivable Area

<p><b><span data-ke-size="size20">Traffic Light Detection 관련</span></b></p><p>해외 신호등이지만 자세한 내용 없이 이미지와 영상만 제공</p><p><a href="https://github.com/farukalamai/traffic-lights-detection-and-color-recognition-using-yolov8/tree/main" target="_blank" class="ke-link">https://github.com/farukalamai/traffic-lights-detection-and-color-recognition-using-yolov8/tree/main</a></p><div class="figure-open" contenteditable="false" data-ke-type="opengraph" data-ke-align="alignCenter" data-og-type="website" data-og-title="GitHub - farukalamai/traffic-lights-detection-and-color-recognition-using-yolov8: traffic-lights-detection-and-color-recognition" data-og-description="traffic-lights-detection-and-color-recognition-using-yolov8 - farukalamai/traffic-lights-detection-and-color-recognition-using-yolov8" data-og-host="github.com" data-og-source-url="https://github.com/farukalamai/traffic-lights-detection-and-color-recognition-using-yolov8/tree/main" data-og-url="https://github.com/farukalamai/traffic-lights-detection-and-color-recognition-using-yolov8" data-og-image="https://scrap.kakaocdn.net/dn/BLTr6/hyYTnuB6pJ/w5m5yK3TEVZu2btfc6Oa9k/img.png?width=1200&height=600&face=0_0_1200_600,https://scrap.kakaocdn.net/dn/pthxM/hyYRsjAJfz/IpWvlSCErfeCX9hsNK2C90/img.png?width=1200&height=600&face=0_0_1200_600"><a href="https://github.com/farukalamai/traffic-lights-detection-and-color-recognition-using-yolov8/tree/main" target="_blank" data-source-url="https://github.com/farukalamai/traffic-lights-detection-and-color-recognition-using-yolov8/tree/main"><div class="og-image"><img class="thumb_img" src="https://scrap.kakaocdn.net/dn/BLTr6/hyYTnuB6pJ/w5m5yK3TEVZu2btfc6Oa9k/img.png?width=1200&height=600&face=0_0_1200_600,https://scrap.kakaocdn.net/dn/pthxM/hyYRsjAJfz/IpWvlSCErfeCX9hsNK2C90/img.png?width=1200&height=600&face=0_0_1200_600" alt="" xxonerror="this.src="//img1.kakaocdn.net/thumb/C200x200/?fname=https%3A%2F%2Ft1.daumcdn.net%2Fcafe_image%2Fcafe_meta_image_190529.png""></div><div class="og-text"><p class="og-title">GitHub - farukalamai/traffic-lights-detection-and-color-recognition-using-yolov8: traffic-lights-detection-and-color-recognition</p><p class="og-desc">traffic-lights-detection-and-color-recognition-using-yolov8 - farukalamai/traffic-lights-detection-and-color-recognition-using-yolov8</p><p class="og-host">github.com</p></div></a></div><p> </p><p> </p><p>모델까지는 제공</p><p><a href="https://github.com/Syazvinski/Traffic-Light-Detection-Color-Classification" target="_blank" class="ke-link">https://github.com/Syazvinski/Traffic-Light-Detection-Color-Classification</a></p><div class="figure-open" contenteditable="false" data-ke-type="opengraph" data-ke-align="alignCenter" data-og-type="website" data-og-title="GitHub - Syazvinski/Traffic-Light-Detection-Color-Classification: 3 models trained with Yolo v8 that detect traffic lights and a" data-og-description="3 models trained with Yolo v8 that detect traffic lights and also classify thier color. - Syazvinski/Traffic-Light-Detection-Color-Classification" data-og-host="github.com" data-og-source-url="https://github.com/Syazvinski/Traffic-Light-Detection-Color-Classification" data-og-url="https://github.com/Syazvinski/Traffic-Light-Detection-Color-Classification" data-og-image="https://scrap.kakaocdn.net/dn/bHEK0k/hyYRkTnrvw/n9q6rzSKNUHmcDO3x5flK0/img.png?width=1200&height=600&face=0_0_1200_600,https://scrap.kakaocdn.net/dn/cywy6V/hyYVeqrTbx/K4P4mrNfK7K31d2Fku9TBk/img.png?width=1200&height=600&face=0_0_1200_600"><a href="https://github.com/Syazvinski/Traffic-Light-Detection-Color-Classification" target="_blank" data-source-url="https://github.com/Syazvinski/Traffic-Light-Detection-Color-Classification"><div class="og-image"><img class="thumb_img" src="https://scrap.kakaocdn.net/dn/bHEK0k/hyYRkTnrvw/n9q6rzSKNUHmcDO3x5flK0/img.png?width=1200&height=600&face=0_0_1200_600,https://scrap.kakaocdn.net/dn/cywy6V/hyYVeqrTbx/K4P4mrNfK7K31d2Fku9TBk/img.png?width=1200&height=600&face=0_0_1200_600" alt="" xxonerror="this.src="//img1.kakaocdn.net/thumb/C200x200/?fname=https%3A%2F%2Ft1.daumcdn.net%2Fcafe_image%2Fcafe_meta_image_190529.png""></div><div class="og-text"><p class="og-title">GitHub - Syazvinski/Traffic-Light-Detection-Color-Classification: 3 models trained with Yolo v8 that detect traffic lights and a</p><p class="og-desc">3 models trained with Yolo v8 that detect traffic lights and also classify thier color. - Syazvinski/Traffic-Light-Detection-Color-Classification</p><p class="og-host">github.com</p></div></a></div><div class="figure-img" data-ke-type="image" data-ke-style="alignLeft" data-ke-mobilestyle="widthOrigin"><img src="https://t1.daumcdn.net/cafeattach/1RgNt/014304dbf3a472eb1e6dea89963bf69d0ef4dc17_re_1747190053512" class="txc-image" data-img-src="https://t1.daumcdn.net/cafeattach/1RgNt/014304dbf3a472eb1e6dea89963bf69d0ef4dc17_re_1747190053512" data-origin-width="567" data-origin-height="175"><div class="figcaption">정확도 등의 데이터는 제공하지 않음.</div></div><p>YOLOv8를 사용하며 코드도 제공</p><p><a href="https://github.com/KASTEL-MobilityLab/traffic-light-detection" target="_blank" class="ke-link">https://github.com/KASTEL-MobilityLab/traffic-light-detection</a></p><div class="figure-open" contenteditable="false" data-ke-type="opengraph" data-ke-align="alignCenter" data-og-type="website" data-og-title="GitHub - KASTEL-MobilityLab/traffic-light-detection" data-og-description="Contribute to KASTEL-MobilityLab/traffic-light-detection development by creating an account on GitHub." data-og-host="github.com" data-og-source-url="https://github.com/KASTEL-MobilityLab/traffic-light-detection" data-og-url="https://github.com/KASTEL-MobilityLab/traffic-light-detection" data-og-image="https://scrap.kakaocdn.net/dn/cNh1Dw/hyYRmwTtEc/NtQa3pIsJ7OQtT3ttJukR0/img.png?width=1200&height=600&face=0_0_1200_600,https://scrap.kakaocdn.net/dn/c5tNhQ/hyYTnH97SZ/kwagHxDbtWaGa8fJxKRfk1/img.png?width=1200&height=600&face=0_0_1200_600"><a href="https://github.com/KASTEL-MobilityLab/traffic-light-detection" target="_blank" data-source-url="https://github.com/KASTEL-MobilityLab/traffic-light-detection"><div class="og-image"><img class="thumb_img" src="https://scrap.kakaocdn.net/dn/cNh1Dw/hyYRmwTtEc/NtQa3pIsJ7OQtT3ttJukR0/img.png?width=1200&height=600&face=0_0_1200_600,https://scrap.kakaocdn.net/dn/c5tNhQ/hyYTnH97SZ/kwagHxDbtWaGa8fJxKRfk1/img.png?width=1200&height=600&face=0_0_1200_600" alt="" xxonerror="this.src="//img1.kakaocdn.net/thumb/C200x200/?fname=https%3A%2F%2Ft1.daumcdn.net%2Fcafe_image%2Fcafe_meta_image_190529.png""></div><div class="og-text"><p class="og-title">GitHub - KASTEL-MobilityLab/traffic-light-detection</p><p class="og-desc">Contribute to KASTEL-MobilityLab/traffic-light-detection development by creating an account on GitHub.</p><p class="og-host">github.com</p></div></a></div><div class="figure-img" data-ke-type="image" data-ke-style="alignLeft" data-ke-mobilestyle="widthOrigin"><img src="https://t1.daumcdn.net/cafeattach/1RgNt/600bf61f70798b89a6de6e9f5b21721ba2260865_re_1747190053512" class="txc-image" data-img-src="https://t1.daumcdn.net/cafeattach/1RgNt/600bf61f70798b89a6de6e9f5b21721ba2260865_re_1747190053512" data-origin-width="709" data-origin-height="175"></div><p> </p><p><b><span data-ke-size="size20">Line Lane 관련</span></b></p><p> </p><p>UNet을 사용하는 Line Segment</p><p><a href="https://github.com/srianumakonda/Lane-Detection-in-CARLA" target="_blank" class="ke-link">https://github.com/srianumakonda/Lane-Detection-in-CARLA</a></p><div class="figure-open" contenteditable="false" data-ke-type="opengraph" data-ke-align="alignCenter" data-og-type="website" data-og-title="GitHub - srianumakonda/Lane-Detection-in-CARLA" data-og-description="Contribute to srianumakonda/Lane-Detection-in-CARLA development by creating an account on GitHub." data-og-host="github.com" data-og-source-url="https://github.com/srianumakonda/Lane-Detection-in-CARLA" data-og-url="https://github.com/srianumakonda/Lane-Detection-in-CARLA" data-og-image="https://scrap.kakaocdn.net/dn/cYMhvB/hyYTcNoRzT/koJYFVqp9Df4vnENUxSyg0/img.png?width=1200&height=600&face=1005_133_1046_178,https://scrap.kakaocdn.net/dn/iUpV9/hyYU60fnUr/AKBXKYDQtCUkqlXAAakOCk/img.png?width=1200&height=600&face=1005_133_1046_178"><a href="https://github.com/srianumakonda/Lane-Detection-in-CARLA" target="_blank" data-source-url="https://github.com/srianumakonda/Lane-Detection-in-CARLA"><div class="og-image"><img class="thumb_img" src="https://scrap.kakaocdn.net/dn/cYMhvB/hyYTcNoRzT/koJYFVqp9Df4vnENUxSyg0/img.png?width=1200&height=600&face=1005_133_1046_178,https://scrap.kakaocdn.net/dn/iUpV9/hyYU60fnUr/AKBXKYDQtCUkqlXAAakOCk/img.png?width=1200&height=600&face=1005_133_1046_178" alt="" xxonerror="this.src="//img1.kakaocdn.net/thumb/C200x200/?fname=https%3A%2F%2Ft1.daumcdn.net%2Fcafe_image%2Fcafe_meta_image_190529.png""></div><div class="og-text"><p class="og-title">GitHub - srianumakonda/Lane-Detection-in-CARLA</p><p class="og-desc">Contribute to srianumakonda/Lane-Detection-in-CARLA development by creating an account on GitHub.</p><p class="og-host">github.com</p></div></a></div><p> </p><p> </p><p>Carla Lane Dataset 수집 Github</p><p><a href="https://github.com/Glutamat42/Carla-Lane-Detection-Dataset-Generation" target="_blank" class="ke-link">https://github.com/Glutamat42/Carla-Lane-Detection-Dataset-Generation</a></p><div class="figure-open" contenteditable="false" data-ke-type="opengraph" data-ke-align="alignCenter" data-og-type="website" data-og-title="GitHub - Glutamat42/Carla-Lane-Detection-Dataset-Generation: Create a dataset to train a lane detection neural network with CARL" data-og-description="Create a dataset to train a lane detection neural network with CARLA - Glutamat42/Carla-Lane-Detection-Dataset-Generation" data-og-host="github.com" data-og-source-url="https://github.com/Glutamat42/Carla-Lane-Detection-Dataset-Generation" data-og-url="https://github.com/Glutamat42/Carla-Lane-Detection-Dataset-Generation" data-og-image="https://scrap.kakaocdn.net/dn/coUnx8/hyYVfbOcsG/fkoBrsGrvrsNQwwSTPGu8K/img.png?width=1200&height=600&face=0_0_1200_600,https://scrap.kakaocdn.net/dn/eTE4s/hyYTiNC7kk/QT2ITiAufBus5hkN7oNao0/img.png?width=1200&height=600&face=0_0_1200_600"><a href="https://github.com/Glutamat42/Carla-Lane-Detection-Dataset-Generation" target="_blank" data-source-url="https://github.com/Glutamat42/Carla-Lane-Detection-Dataset-Generation"><div class="og-image"><img class="thumb_img" src="https://scrap.kakaocdn.net/dn/coUnx8/hyYVfbOcsG/fkoBrsGrvrsNQwwSTPGu8K/img.png?width=1200&height=600&face=0_0_1200_600,https://scrap.kakaocdn.net/dn/eTE4s/hyYTiNC7kk/QT2ITiAufBus5hkN7oNao0/img.png?width=1200&height=600&face=0_0_1200_600" alt="" xxonerror="this.src="//img1.kakaocdn.net/thumb/C200x200/?fname=https%3A%2F%2Ft1.daumcdn.net%2Fcafe_image%2Fcafe_meta_image_190529.png""></div><div class="og-text"><p class="og-title">GitHub - Glutamat42/Carla-Lane-Detection-Dataset-Generation: Create a dataset to train a lane detection neural network with CARL</p><p class="og-desc">Create a dataset to train a lane detection neural network with CARLA - Glutamat42/Carla-Lane-Detection-Dataset-Generation</p><p class="og-host">github.com</p></div></a></div><p> </p><p>참고용 kaggle</p><p><a href="https://www.kaggle.com/datasets/thomasfermi/lane-detection-for-carla-driving-simulator" target="_blank" class="ke-link">https://www.kaggle.com/datasets/thomasfermi/lane-detection-for-carla-driving-simulator</a></p><div class="figure-open" contenteditable="false" data-ke-type="opengraph" data-ke-align="alignCenter" data-og-type="website" data-og-title="Lane Detection for Carla Driving Simulator" data-og-description="semantic segmentation for lane boundaries enables automated driving" data-og-host="www.kaggle.com" data-og-source-url="https://www.kaggle.com/datasets/thomasfermi/lane-detection-for-carla-driving-simulator" data-og-url="https://www.kaggle.com/datasets/thomasfermi/lane-detection-for-carla-driving-simulator" data-og-image="https://scrap.kakaocdn.net/dn/C6Sx0/hyYU2cuimO/IjLoAVKiYJqWl1d3RplfM1/img.jpg?width=1200&height=1200&face=0_0_1200_1200"><a href="https://www.kaggle.com/datasets/thomasfermi/lane-detection-for-carla-driving-simulator" target="_blank" data-source-url="https://www.kaggle.com/datasets/thomasfermi/lane-detection-for-carla-driving-simulator"><div class="og-image"><img class="thumb_img" src="https://scrap.kakaocdn.net/dn/C6Sx0/hyYU2cuimO/IjLoAVKiYJqWl1d3RplfM1/img.jpg?width=1200&height=1200&face=0_0_1200_1200" alt="" xxonerror="this.src="//img1.kakaocdn.net/thumb/C200x200/?fname=https%3A%2F%2Ft1.daumcdn.net%2Fcafe_image%2Fcafe_meta_image_190529.png""></div><div class="og-text"><p class="og-title">Lane Detection for Carla Driving Simulator</p><p class="og-desc">semantic segmentation for lane boundaries enables automated driving</p><p class="og-host">www.kaggle.com</p></div></a></div><p> </p><p><span data-ke-size="size20"><b>Drivable Area 관련</b></span></p><p><span data-ke-size="size16">Deeplabv3+를 사용한 Segment</span></p><p><a href="https://github.com/sunggukcha/deeplabs" target="_blank" class="ke-link">https://github.com/sunggukcha/deeplabs</a></p><div class="figure-open" contenteditable="false" data-ke-type="opengraph" data-ke-align="alignCenter" data-og-type="website" data-og-title="GitHub - sunggukcha/deeplabs: Deeplabv3(+) for BDD100k drivable area" data-og-description="Deeplabv3(+) for BDD100k drivable area. Contribute to sunggukcha/deeplabs development by creating an account on GitHub." data-og-host="github.com" data-og-source-url="https://github.com/sunggukcha/deeplabs" data-og-url="https://github.com/sunggukcha/deeplabs" data-og-image="https://scrap.kakaocdn.net/dn/gVumT/hyYVejFXyP/XiWh5CkYtmvuYClSkywAu0/img.png?width=1200&height=600&face=0_0_1200_600,https://scrap.kakaocdn.net/dn/K7i54/hyYTi7WhOt/Hw0M6diyQRQXvMYOSAEAp1/img.png?width=1200&height=600&face=0_0_1200_600"><a href="https://github.com/sunggukcha/deeplabs" target="_blank" data-source-url="https://github.com/sunggukcha/deeplabs"><div class="og-image"><img class="thumb_img" src="https://scrap.kakaocdn.net/dn/gVumT/hyYVejFXyP/XiWh5CkYtmvuYClSkywAu0/img.png?width=1200&height=600&face=0_0_1200_600,https://scrap.kakaocdn.net/dn/K7i54/hyYTi7WhOt/Hw0M6diyQRQXvMYOSAEAp1/img.png?width=1200&height=600&face=0_0_1200_600" alt="" xxonerror="this.src="//img1.kakaocdn.net/thumb/C200x200/?fname=https%3A%2F%2Ft1.daumcdn.net%2Fcafe_image%2Fcafe_meta_image_190529.png""></div><div class="og-text"><p class="og-title">GitHub - sunggukcha/deeplabs: Deeplabv3(+) for BDD100k drivable area</p><p class="og-desc">Deeplabv3(+) for BDD100k drivable area. Contribute to sunggukcha/deeplabs development by creating an account on GitHub.</p><p class="og-host">github.com</p></div></a></div><p>UNet을 사용한 Segment</p><p><a href="https://github.com/AnshChoudhary/U-Net-Drivable-Area-Segmentation" target="_blank" class="ke-link">https://github.com/AnshChoudhary/U-Net-Drivable-Area-Segmentation</a></p><div class="figure-open" contenteditable="false" data-ke-type="opengraph" data-ke-align="alignCenter" data-og-type="website" data-og-title="GitHub - AnshChoudhary/U-Net-Drivable-Area-Segmentation" data-og-description="Contribute to AnshChoudhary/U-Net-Drivable-Area-Segmentation development by creating an account on GitHub." data-og-host="github.com" data-og-source-url="https://github.com/AnshChoudhary/U-Net-Drivable-Area-Segmentation" data-og-url="https://github.com/AnshChoudhary/U-Net-Drivable-Area-Segmentation" data-og-image="https://scrap.kakaocdn.net/dn/brVzuv/hyYRvtQsuR/RnS6VY7jQcMahg0kkUJAWk/img.png?width=1200&height=600&face=1006_142_1049_190,https://scrap.kakaocdn.net/dn/W4YFH/hyYVce5MUh/STQp81LrblfHBBSxK5cOPK/img.png?width=1200&height=600&face=1006_142_1049_190"><a href="https://github.com/AnshChoudhary/U-Net-Drivable-Area-Segmentation" target="_blank" data-source-url="https://github.com/AnshChoudhary/U-Net-Drivable-Area-Segmentation"><div class="og-image"><img class="thumb_img" src="https://scrap.kakaocdn.net/dn/brVzuv/hyYRvtQsuR/RnS6VY7jQcMahg0kkUJAWk/img.png?width=1200&height=600&face=1006_142_1049_190,https://scrap.kakaocdn.net/dn/W4YFH/hyYVce5MUh/STQp81LrblfHBBSxK5cOPK/img.png?width=1200&height=600&face=1006_142_1049_190" alt="" xxonerror="this.src="//img1.kakaocdn.net/thumb/C200x200/?fname=https%3A%2F%2Ft1.daumcdn.net%2Fcafe_image%2Fcafe_meta_image_190529.png""></div><div class="og-text"><p class="og-title">GitHub - AnshChoudhary/U-Net-Drivable-Area-Segmentation</p><p class="og-desc">Contribute to AnshChoudhary/U-Net-Drivable-Area-Segmentation development by creating an account on GitHub.</p><p class="og-host">github.com</p></div></a></div><p> </p><p> </p><p> </p><p> </p><p>통합 버전의 ZOO model 차선 검출은 아직 서비스되지 않지만 그 외 여러가지 기능을 제공함</p><p><a href="https://github.com/SysCV/bdd100k-models" target="_blank" class="ke-link">https://github.com/SysCV/bdd100k-models</a></p><div class="figure-img" data-ke-type="image" data-ke-style="alignCenter" data-ke-mobilestyle="widthOrigin"><img src="https://t1.daumcdn.net/cafeattach/1RgNt/15d78cfec9277f3aec09f71473021802f87a1bc7_re_1747190053511" class="txc-image" data-img-src="https://t1.daumcdn.net/cafeattach/1RgNt/15d78cfec9277f3aec09f71473021802f87a1bc7_re_1747190053511" data-origin-width="1009" data-origin-height="339"></div><p> </p><p>BDD100K Segment에 대한 GIthub</p><p><a href="https://github.com/vincentpalma/Efficient-Segmentation-Networks-BDD100K" target="_blank" class="ke-link">https://github.com/vincentpalma/Efficient-Segmentation-Networks-BDD100K</a></p><div class="figure-open" contenteditable="false" data-ke-type="opengraph" data-ke-align="alignCenter" data-og-type="website" data-og-title="GitHub - vincentpalma/Efficient-Segmentation-Networks-BDD100K: Lightweight models for real-time semantic segmentationon PyTorch " data-og-description="Lightweight models for real-time semantic segmentationon PyTorch (include SQNet, LinkNet, SegNet, UNet, ENet, ERFNet, EDANet, ESPNet, ESPNetv2, LEDNet, ESNet, FSSNet, CGNet, DABNet, Fast-SCNN, Cont..." data-og-host="github.com" data-og-source-url="https://github.com/vincentpalma/Efficient-Segmentation-Networks-BDD100K" data-og-url="https://github.com/vincentpalma/Efficient-Segmentation-Networks-BDD100K" data-og-image="https://scrap.kakaocdn.net/dn/q67zD/hyYTfQT67p/CD8NqSnP7pH1mZpvZnr4uk/img.png?width=1200&height=600&face=0_0_1200_600,https://scrap.kakaocdn.net/dn/cSHenT/hyYU7LClM1/0girqIUpbXzbiGvvMM15KK/img.png?width=1200&height=600&face=0_0_1200_600"><a href="https://github.com/vincentpalma/Efficient-Segmentation-Networks-BDD100K" target="_blank" data-source-url="https://github.com/vincentpalma/Efficient-Segmentation-Networks-BDD100K"><div class="og-image"><img class="thumb_img" src="https://scrap.kakaocdn.net/dn/q67zD/hyYTfQT67p/CD8NqSnP7pH1mZpvZnr4uk/img.png?width=1200&height=600&face=0_0_1200_600,https://scrap.kakaocdn.net/dn/cSHenT/hyYU7LClM1/0girqIUpbXzbiGvvMM15KK/img.png?width=1200&height=600&face=0_0_1200_600" alt="" xxonerror="this.src="//img1.kakaocdn.net/thumb/C200x200/?fname=https%3A%2F%2Ft1.daumcdn.net%2Fcafe_image%2Fcafe_meta_image_190529.png""></div><div class="og-text"><p class="og-title">GitHub - vincentpalma/Efficient-Segmentation-Networks-BDD100K: Lightweight models for real-time semantic segmentationon PyTorch </p><p class="og-desc">Lightweight models for real-time semantic segmentationon PyTorch (include SQNet, LinkNet, SegNet, UNet, ENet, ERFNet, EDANet, ESPNet, ESPNetv2, LEDNet, ESNet, FSSNet, CGNet, DABNet, Fast-SCNN, Cont...</p><p class="og-host">github.com</p></div></a></div><p> </p><div class="figure-img" data-ke-type="image" data-ke-style="alignLeft" data-ke-mobilestyle="widthOrigin"><img src="https://t1.daumcdn.net/cafeattach/1RgNt/f37875cfee87c5f5d05b055b9f069ef13ca277c0_re_1747190053512" class="txc-image" data-img-src="https://t1.daumcdn.net/cafeattach/1RgNt/f37875cfee87c5f5d05b055b9f069ef13ca277c0_re_1747190053512" data-origin-width="815" data-origin-height="555"></div><p>BDD100k와 cityscapes 등의 여러 데이터셋을 종합적으로 학습한 것으로 보임.</p><p>(모델의 크기가 커서 임베디드 시스템에서 수행하기에는 부적합.)</p>