![]() ![]() But how do I make it learn to "see" what's in the picture? Any help would be appreciated. I figure it's somehow learning to detect the edges of the images since the labeling is around the whole image. It puts a huge bounding box around the entirety of the image like it's trained to detect only the edges of the image. csv and running the training until the loss stops decreasing my detection on my test set are awful. The format of the labeling is a csv file with these entries: filename, width, height, class, xmin, ymin, xmax, ymax. If there's a way to send whole images without labeling them too be trained using tensorflow api I didn't find it but I thought making a program that labels the whole image would not be that hard. But I wanted to increase the number of images I train with, however the labeling process is long and boring so I found a data set with cropped images, so only my object is in the image. Let us identify your products and update your drivers Get Started. ![]() Intel Compute Stick with Intel Atom Processors. Intel Compute Stick with 6th Generation Intel Core Processors. I made it detect my object fairly well with a small number of images. Intel NUC Board with Intel Atom Processors. So I've been messing around with tensorflow's object detection api and specifically the re-training of models, essentially doing this. ![]()
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