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In this real-case scenario, an advanced Computer Vision project successfully tracks the tip of a glowing steel bar using color-based tracking techniques with OpenCV.
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This project tackles a real-world challenge of automating client document processing, with a focus on enhancing document classification, error detection, data extraction, and validation.
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Object detection YOLOv5m finetuning on custom dataset with PyTorch. The custom dataset was labeled in CVAT and preprocessed in Roboflow. Data augmentation is implemented in the last experiments. In…
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Finetuning-Stable-Diffusion Public
Finetuning Stable Diffusion 2.0 and Stable Diffusion 1.5
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Stable Diffusion is a text-to-image latent diffusion model created by the researchers and engineers from CompVis, Stability AI and LAION. It is trained on 512x512 images from a subset of the LAION-…
Jupyter Notebook UpdatedAug 24, 2022 -
Multiclass semantic segmentation using U-Net with Keras.
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Binary semantic segmentation using U-Net (in Keras)
Jupyter Notebook UpdatedAug 13, 2022 -
Object detection YOLOv5m training on custom dataset with PyTorch using Transfer Learning and Fine Tuning. Inference on videos.
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GANs-with-limited-data Public
BigGAN training with limited data using Transfer Learning, Data Augmentation and Conistency Regularization.
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Object detection with MobileNet SSD, pretrained on the MS COCO dataset and fine-tuned on PASCAL VOC, implemented with OpenCV.
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