![]() We now must be careful because "lush" in my own language does not exist as far as I know working with the sound of the word only, there is softness in it. This is no problem, unless you hold something against it which has the properties of "lush". Combine all these and you have a most clear sounding cable but which also can be bitchy. (this is the description I already made on June 1 - the description above I just created again, objectively)Īll is relative and for me the sound is relative to Clairixa Ĭlairixa, as her name tells, is clarity, crystal and clear water. But now with the advantage of the dynamics and "no noise" from digital. Actually, when listening to the Lush, what should come to mind is the analogy with analog : And it is right here where the difference with Clairixa is : Clairixa shows the lesser parts (from the source) or it just is the lesser cable for some material or sounds. There hasn't been one single time in the 4 weeks I am listening to the Lush now, that I was disturbed by one or the other things which urged for improvement. But there's a "connecting droop" that turns digital into analog. Again it is so that the cable is as fresh as nowadays is required. All "tones" swing.Īgain it is so that all detail remains. Well, yes Of course I am inclined to say that it is the harmonisation of the musicans etc., but while this would be completely the truth, it is about the technical thing underlying that. If you hear it right out of the box there will be one thing jumping at you right away : the harmonisation of. Oh, I almost forgot : the last trajectory has been the listening for 4 weeks.Ĭlairixa is the best 1:1 translation from digital.Ĭlairixa is a most pinpointed razor blade sharp machine. This includes the sleeve which actually is part of the topology again (it is a dielectric). Lastly a topology had to be determined which would make it feasible to ever construct the cable. Then the margin was determined as in "too soft now" or "nice but too strange". Then the direction was determined of which way specifications were allowed to go (think a simple plus x or minus x here). Yes, you heard me right, I said sound (as in : let's drop the "quality" part). It would anyway be very hard to accomplish.īut who actually tells that the USB specification with its - mind you - wide margin can't be improved for Audio ?įirst it took two months or so of throughput before I found how specifications as such would influence the sound. Well, it actually is It is well possible that nothing was made better to USB spec than the Clairixa. Some say the Clairixa is the best USB Cable ever. If you look closely you see how The Lush operates. But it is also about wealth in the sense of a wealth of things. When I myself think about "lush" as such, it is something which is soft. And as you can imagine, it gets more and more difficult to improve. We will convert the txt file into pandas dataframe.As you can see I try to keep ahead of things. The ground truth file contains the image filename, bounding box coordinates which contain the left, top, right, and bottom coordinates of traffic signs present in the image, and the class id of the traffic sign. The dataset also contains a text file that is in CSV format and consists of the ground truth for all traffic signs in the images. The dataset consists of 900 images in ppm format. The higher the IoU, the better the performance. Using it, we can figure out how well does our predicted bounding box overlaps with the ground truth bounding box. It helps us benchmark the accuracy of our model predictions. We will use IOU as an evaluation metric here. We will use object detection models to detect the traffic signs in this problem statement. we need to build a solution such that the model should be able to detect the signs within seconds. There is a latency requirement for this problem. The objective is to detect traffic signs that are present inside an image. The objective of this case study is to detect traffic signs and classify them. ![]() Even autonomous vehicle companies are recently working on upgrading their traffic lights and stop signs detecting techniques. Traffic sign detection is a challenging real-world problem of high industrial relevance. We will be discussing the problem statement from exploratory data analysis to pipeline deployment.
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