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EuCanna is a self-hosted darknet site that offers various medicinal remedies, including bath melts, skin creams, suppositories, soaps, etc. All of the goods available on the site contain the finest Rick Simpson oil that is widely known for its therapeutic qualities.

HQER is a darknet market that sells high-end counterfeit Euro bills. The store claims that its banknotes are manufactured from cotton-based paper and easily pass all the pen tests. Among other claims, it is suggested that the notes are incorporated with UVI to ensure the passing of the test.

All the crucial buyer security measures are included. The products are shipped from France and express shipping is free. NLGrowers is another darknet Tor-based cannabis store. The store ships within 24 hours from payment. There are quite a few happy users on the darknet links Reddit, so you may get some advice there before buying anything from the store.

BitPharma is a reputed alternative darknet controlled substances market. The goods users can get from the store include stimulants, prescription medicines, and psychedelics. Orders for over Euros are shipped for free. The store provides shipping to France and Germany. We Fight Censorship is basically a darknet training blog.

The content published is available in original languages, including Arabic, Chinese, Spanish, and Russian, as well as in English and French translations. The posts of the blog include darknet websites, photos, articles, videos, and sound files. Darknet is an immense space of information.

There are, of course, far more. Darknet Reddit is a very nice source of relevant information, where users share their experiences with tons of dark web sites and shops, so you can draw relevant conclusions. Web researcher. Bacon master. Liquor aficionado. Mastermind, Hacker. Remember Me. The Dark Web. Home News Technology All Hosting. Home Dark Web. February 24, Reading Time: 11min read. Share on Facebook Share on Twitter.

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Login to your account below. Forgotten Password? Create New Account! Fill the forms below to register. All fields are required. Log In. YOLOv3 is extremely fast and accurate. In mAP measured at. Moreover, you can easily tradeoff between speed and accuracy simply by changing the size of the model, no retraining required! Prior detection systems repurpose classifiers or localizers to perform detection. They apply the model to an image at multiple locations and scales.

High scoring regions of the image are considered detections. We use a totally different approach. We apply a single neural network to the full image. This network divides the image into regions and predicts bounding boxes and probabilities for each region. These bounding boxes are weighted by the predicted probabilities. Our model has several advantages over classifier-based systems. It looks at the whole image at test time so its predictions are informed by global context in the image.

It also makes predictions with a single network evaluation unlike systems like R-CNN which require thousands for a single image. See our paper for more details on the full system. YOLOv3 uses a few tricks to improve training and increase performance, including: multi-scale predictions, a better backbone classifier, and more. The full details are in our paper! This post will guide you through detecting objects with the YOLO system using a pre-trained model.

Or instead of reading all that just run:. You will have to download the pre-trained weight file here MB. Or just run this:. Darknet prints out the objects it detected, its confidence, and how long it took to find them.

Instead, it saves them in predictions. You can open it to see the detected objects. Since we are using Darknet on the CPU it takes around seconds per image. If we use the GPU version it would be much faster.

The detect command is shorthand for a more general version of the command. It is equivalent to the command:. Instead of supplying an image on the command line, you can leave it blank to try multiple images in a row.