Hello, I have a project to do. We will be given camera images of a traffic from different angles. We need to create a 3D model of the scene with capture the photos, pre-processing, 3D reconstruction and 3D modeling applications, respectively. We are asked to use only Python. Vehicles are the object we want to focus on in the video. But we still haven't been able to come up with a roadmap in our minds yet. With colors etc. to make a better 3D model with frames. We'll have to play. We understand that. We can detect keypoints that match with SIFT, and we understand that. Then it felt like we could use SfM. The only thing we don't understand is that the vehicles are in motion. The image of the vehicle in motion changes in every frame. We just couldn't figure out how to do this.
appreciated :) Would be nice to compare the execution speed (FPS) for the same application in C++, for the first code example, SubstractorKNN, just to see how much difference in performance between python and C++, not for python in general but only for opencv+numpy. Thanks in advance
Thank you! Yes it would actually be cool to test, i might do a video about that. My guess would be that when only using the opencv function and only 1 algorithm in this case, the fps will be similar since it's all implemented in c++
Hello, I have a project to do. We will be given camera images of a traffic from different angles. We need to create a 3D model of the scene with capture the photos, pre-processing, 3D reconstruction and 3D modeling applications, respectively. We are asked to use only Python. Vehicles are the object we want to focus on in the video. But we still haven't been able to come up with a roadmap in our minds yet. With colors etc. to make a better 3D model with frames. We'll have to play. We understand that. We can detect keypoints that match with SIFT, and we understand that. Then it felt like we could use SfM. The only thing we don't understand is that the vehicles are in motion. The image of the vehicle in motion changes in every frame. We just couldn't figure out how to do this. We would be appreciated If you can give a roadmap to us. Greetings
23.48 , what's happening from line 31 to 38 sir. Im very confused right now. when you do the diff1 +diff2, it will get 0 right? also line no 28 and 29 sir
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Hello, I have a project to do. We will be given camera images of a traffic from different angles. We need to create a 3D model of the scene with capture the photos, pre-processing, 3D reconstruction and 3D modeling applications, respectively. We are asked to use only Python. Vehicles are the object we want to focus on in the video. But we still haven't been able to come up with a roadmap in our minds yet. With colors etc. to make a better 3D model with frames. We'll have to play. We understand that. We can detect keypoints that match with SIFT, and we understand that. Then it felt like we could use SfM. The only thing we don't understand is that the vehicles are in motion. The image of the vehicle in motion changes in every frame. We just couldn't figure out how to do this.
how did it go dude?
Excellent video tutorial.
Thanks a lot!
Nice to see a video by somebody that is a genuine subject matter expert. Great work.
can you do stauffer grimson's background subtraction code, which uses gaussian mixture and online update of parameters
appreciated :)
Would be nice to compare the execution speed (FPS) for the same application in C++, for the first code example, SubstractorKNN, just to see how much difference in performance between python and C++, not for python in general but only for opencv+numpy. Thanks in advance
Thank you! Yes it would actually be cool to test, i might do a video about that. My guess would be that when only using the opencv function and only 1 algorithm in this case, the fps will be similar since it's all implemented in c++
Hello, I have a project to do. We will be given camera images of a traffic from different angles. We need to create a 3D model of the scene with capture the photos, pre-processing, 3D reconstruction and 3D modeling applications, respectively. We are asked to use only Python. Vehicles are the object we want to focus on in the video. But we still haven't been able to come up with a roadmap in our minds yet. With colors etc. to make a better 3D model with frames. We'll have to play. We understand that. We can detect keypoints that match with SIFT, and we understand that. Then it felt like we could use SfM. The only thing we don't understand is that the vehicles are in motion. The image of the vehicle in motion changes in every frame. We just couldn't figure out how to do this. We would be appreciated If you can give a roadmap to us. Greetings
23.48 , what's happening from line 31 to 38 sir. Im very confused right now. when you do the diff1 +diff2, it will get 0 right?
also line no 28 and 29 sir