TensorFlow2.0-Examples
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YunYang1994
YOLOv3 model doesn't converge
Hello. First of all, thank you for your amazing code. While trying to train the YOLOv3 model from scratch on yymnist dataset, I noticed that the loss is fluctuating between 20 and 40 and it doesn't converge. I didnt't change any of the config settings except the _C.YOLO.classes = "data/classes/voc.names" which I changed it to _C.YOLO.classes = "data/classes/yymnist.names". Am I doing something wrong? I use tensorflow==2.5.0
Hello. First of all, thank you for your amazing code. While trying to train the YOLOv3 model from scratch on yymnist dataset, I noticed that the loss is fluctuating between 20 and 40 and it doesn't converge. I didnt't change any of the config settings except the _C.YOLO.classes = "data/classes/voc.names" which I changed it to _C.YOLO.classes = "data/classes/yymnist.names". Am I doing something wrong? I use tensorflow==2.5.0
I met the same situation,Have you solved？
Hello. First of all, thank you for your amazing code. While trying to train the YOLOv3 model from scratch on yymnist dataset, I noticed that the loss is fluctuating between 20 and 40 and it doesn't converge. I didnt't change any of the config settings except the _C.YOLO.classes = "data/classes/voc.names" which I changed it to _C.YOLO.classes = "data/classes/yymnist.names". Am I doing something wrong? I use tensorflow==2.5.0
I met the same situation,Have you solved？
I solved the problem by using tensorflow 2.2.0. It turned out that in tensorflow 2.5.0 which I was using, after the first prediction, the weights somehow got random and the only true prediction was for the first test image and then the weights got random. When I used tensorflow 2.2.0 the issue was solved. however, I was able to solve the issue in tensorflow 2.5.0 by freezing the weghts after loading the model.
I was gonna close the issue, so let me know if your problem is solved.
Hello. First of all, thank you for your amazing code. While trying to train the YOLOv3 model from scratch on yymnist dataset, I noticed that the loss is fluctuating between 20 and 40 and it doesn't converge. I didnt't change any of the config settings except the _C.YOLO.classes = "data/classes/voc.names" which I changed it to _C.YOLO.classes = "data/classes/yymnist.names". Am I doing something wrong? I use tensorflow==2.5.0
I met the same situation,Have you solved？
I solved the problem by using tensorflow 2.2.0. It turned out that in tensorflow 2.5.0 which I was using, after the first prediction, the weights somehow got random and the only true prediction was for the first test image and then the weights got random. When I used tensorflow 2.2.0 the issue was solved. however, I was able to solve the issue in tensorflow 2.5.0 by freezing the weghts after loading the model.
I was gonna close the issue, so let me know if your problem is solved.
When I run video_demo.py, I met the same problem. Only the first prediction is true, the others are nan. I guess the problem is in the 'utils.load_weights(model, "./yolov3.weights")'. How to solve the problem? I use tensorflow==2.7.0
Hello. First of all, thank you for your amazing code. While trying to train the YOLOv3 model from scratch on yymnist dataset, I noticed that the loss is fluctuating between 20 and 40 and it doesn't converge. I didnt't change any of the config settings except the _C.YOLO.classes = "data/classes/voc.names" which I changed it to _C.YOLO.classes = "data/classes/yymnist.names". Am I doing something wrong? I use tensorflow==2.5.0
I met the same situation,Have you solved？
I solved the problem by using tensorflow 2.2.0. It turned out that in tensorflow 2.5.0 which I was using, after the first prediction, the weights somehow got random and the only true prediction was for the first test image and then the weights got random. When I used tensorflow 2.2.0 the issue was solved. however, I was able to solve the issue in tensorflow 2.5.0 by freezing the weghts after loading the model.
I was gonna close the issue, so let me know if your problem is solved.
What command did you added and where? Thanks!
Hello. First of all, thank you for your amazing code. While trying to train the YOLOv3 model from scratch on yymnist dataset, I noticed that the loss is fluctuating between 20 and 40 and it doesn't converge. I didnt't change any of the config settings except the _C.YOLO.classes = "data/classes/voc.names" which I changed it to _C.YOLO.classes = "data/classes/yymnist.names". Am I doing something wrong? I use tensorflow==2.5.0
I met the same situation,Have you solved？
I solved the problem by using tensorflow 2.2.0. It turned out that in tensorflow 2.5.0 which I was using, after the first prediction, the weights somehow got random and the only true prediction was for the first test image and then the weights got random. When I used tensorflow 2.2.0 the issue was solved. however, I was able to solve the issue in tensorflow 2.5.0 by freezing the weghts after loading the model. I was gonna close the issue, so let me know if your problem is solved.
When I run video_demo.py, I met the same problem. Only the first prediction is true, the others are nan. I guess the problem is in the 'utils.load_weights(model, "./yolov3.weights")'. How to solve the problem? I use tensorflow==2.7.0
One way that helped me fix this issue was down-grading tensorflow to 2.2.0. Another solution wich I found was freezing the weights after loading them. These two solutions was helpful for me.
Hello. First of all, thank you for your amazing code. While trying to train the YOLOv3 model from scratch on yymnist dataset, I noticed that the loss is fluctuating between 20 and 40 and it doesn't converge. I didnt't change any of the config settings except the _C.YOLO.classes = "data/classes/voc.names" which I changed it to _C.YOLO.classes = "data/classes/yymnist.names". Am I doing something wrong? I use tensorflow==2.5.0
I met the same situation,Have you solved？
I solved the problem by using tensorflow 2.2.0. It turned out that in tensorflow 2.5.0 which I was using, after the first prediction, the weights somehow got random and the only true prediction was for the first test image and then the weights got random. When I used tensorflow 2.2.0 the issue was solved. however, I was able to solve the issue in tensorflow 2.5.0 by freezing the weghts after loading the model. I was gonna close the issue, so let me know if your problem is solved.
What command did you added and where? Thanks!
After you load the weights with model.set_weights(weights) or model.load_weights("path/to/weights"), just add the following command: model.trainable = False