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Steering not turning for the Autopilotv2 and i am using the same run video and same code #3
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Same here. Have you solved your problem? |
Did you succeed in the meantime? |
Yes ita working now.
…On Tue, Nov 5, 2019, 3:37 PM maxmstrmn ***@***.***> wrote:
Did you succeed in the meantime?
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What did you do? Could you share the source code? |
Hi,
I didn't change anything. We just need to delete the label and features
file from the folder and run it again. Load the file again, train it and run the AutopilotV2 file.
…On Fri, Nov 8, 2019, 9:53 PM maxmstrmn ***@***.***> wrote:
What did you do? Could you share the source code?
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Hi, thank you for this hint. But it doesn't work. I only use the v2 files from this repo (which don't include labels), train and test. The final file size of the h5 file is around 8mb, which is wrong as the file shipped in this repo ist 28mb large. |
HI,
Yes it does not have labels and features. You must run load data.py first.
Then it will create labels and features. For that, you must download a
dataset from sully chen and store it inside the Autopilotv2 folder. Then
run train.py. The model will be trained and stored in .h file. After that,
run the AutopilotAppv2.py. It will work
…On Thu, 21 Nov 2019 at 17:56, maxmstrmn ***@***.***> wrote:
Hi, thank you for this hint. But it doesn't work. I only use the v2 files
from this repo (which don't include labels), train and test. The final file
size of the h5 file is around 8mb, which is wrong as the file shipped in
this repo ist 28mb large.
Also if I print the network summary of both files it seems that some
layers are missing in my file...
Which environment do you use?
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Hi, |
No success, even with the larger dataset the final .h5 file is around 8mb large. |
It seems the training is crazy. I printed both model summaries using the print_summary method from the keras utils. As you can see, in my trained model, a lot of layers are missing! Here ist the output: summary .h5 from this repo Layer (type) Output Shape Param #lambda_1 (Lambda) (None, 100, 100, 1) 0 conv2d_1 (Conv2D) (None, 100, 100, 32) 320 activation_1 (Activation) (None, 100, 100, 32) 0 max_pooling2d_1 (MaxPooling2 (None, 50, 50, 32) 0 conv2d_2 (Conv2D) (None, 50, 50, 64) 18496 activation_2 (Activation) (None, 50, 50, 64) 0 max_pooling2d_2 (MaxPooling2 (None, 25, 25, 64) 0 conv2d_3 (Conv2D) (None, 25, 25, 128) 73856 activation_3 (Activation) (None, 25, 25, 128) 0 max_pooling2d_3 (MaxPooling2 (None, 12, 12, 128) 0 flatten_1 (Flatten) (None, 18432) 0 dropout_1 (Dropout) (None, 18432) 0 dense_1 (Dense) (None, 128) 2359424 dense_2 (Dense) (None, 64) 8256 dense_3 (Dense) (None, 1) 65Total params: 2,460,417 summary .h5 from my training output Model: "sequential_1" Layer (type) Output Shape Param #lambda_1 (Lambda) (None, 100, 100, 1) 0 conv2d_1 (Conv2D) (None, 100, 100, 32) 320 activation_1 (Activation) (None, 100, 100, 32) 0 max_pooling2d_1 (MaxPooling2 (None, 50, 50, 32) 0 conv2d_2 (Conv2D) (None, 50, 50, 32) 9248 activation_2 (Activation) (None, 50, 50, 32) 0 max_pooling2d_2 (MaxPooling2 (None, 25, 25, 32) 0 conv2d_3 (Conv2D) (None, 25, 25, 64) 18496 activation_3 (Activation) (None, 25, 25, 64) 0 max_pooling2d_3 (MaxPooling2 (None, 12, 12, 64) 0 conv2d_4 (Conv2D) (None, 12, 12, 64) 36928 activation_4 (Activation) (None, 12, 12, 64) 0 max_pooling2d_4 (MaxPooling2 (None, 6, 6, 64) 0 conv2d_5 (Conv2D) (None, 6, 6, 128) 73856 activation_5 (Activation) (None, 6, 6, 128) 0 max_pooling2d_5 (MaxPooling2 (None, 3, 3, 128) 0 conv2d_6 (Conv2D) (None, 3, 3, 128) 147584 activation_6 (Activation) (None, 3, 3, 128) 0 max_pooling2d_6 (MaxPooling2 (None, 1, 1, 128) 0 flatten_1 (Flatten) (None, 128) 0 dropout_1 (Dropout) (None, 128) 0 dense_1 (Dense) (None, 1024) 132096 dense_2 (Dense) (None, 256) 262400 dense_3 (Dense) (None, 64) 16448 dense_4 (Dense) (None, 1) 65Total params: 697,441 |
Did u try to run the AutopilotV2.py? Is the steering angle turning or still
static?
…On Fri, Nov 22, 2019, 7:29 PM maxmstrmn ***@***.***> wrote:
It seems the training is crazy. I printed both model summaries using the
print_summary method from the keras utils.
Here ist the output:
`summary repo
Model: "sequential_1"
------------------------------
Layer (type) Output Shape Param #
lambda_1 (Lambda) (None, 100, 100, 1) 0
------------------------------
conv2d_1 (Conv2D) (None, 100, 100, 32) 320
------------------------------
activation_1 (Activation) (None, 100, 100, 32) 0
------------------------------
max_pooling2d_1 (MaxPooling2 (None, 50, 50, 32) 0
------------------------------
conv2d_2 (Conv2D) (None, 50, 50, 64) 18496
------------------------------
activation_2 (Activation) (None, 50, 50, 64) 0
------------------------------
max_pooling2d_2 (MaxPooling2 (None, 25, 25, 64) 0
------------------------------
conv2d_3 (Conv2D) (None, 25, 25, 128) 73856
------------------------------
activation_3 (Activation) (None, 25, 25, 128) 0
------------------------------
max_pooling2d_3 (MaxPooling2 (None, 12, 12, 128) 0
------------------------------
flatten_1 (Flatten) (None, 18432) 0
------------------------------
dropout_1 (Dropout) (None, 18432) 0
------------------------------
dense_1 (Dense) (None, 128) 2359424
------------------------------
dense_2 (Dense) (None, 64) 8256
------------------------------
dense_3 (Dense) (None, 1) 65
Total params: 2,460,417
Trainable params: 2,460,417
Non-trainable params: 0
------------------------------
summary my own
Model: "sequential_1"
------------------------------
Layer (type) Output Shape Param #
lambda_1 (Lambda) (None, 100, 100, 1) 0
------------------------------
conv2d_1 (Conv2D) (None, 100, 100, 32) 320
------------------------------
activation_1 (Activation) (None, 100, 100, 32) 0
------------------------------
max_pooling2d_1 (MaxPooling2 (None, 50, 50, 32) 0
------------------------------
conv2d_2 (Conv2D) (None, 50, 50, 32) 9248
------------------------------
activation_2 (Activation) (None, 50, 50, 32) 0
------------------------------
max_pooling2d_2 (MaxPooling2 (None, 25, 25, 32) 0
------------------------------
conv2d_3 (Conv2D) (None, 25, 25, 64) 18496
------------------------------
activation_3 (Activation) (None, 25, 25, 64) 0
------------------------------
max_pooling2d_3 (MaxPooling2 (None, 12, 12, 64) 0
------------------------------
conv2d_4 (Conv2D) (None, 12, 12, 64) 36928
------------------------------
activation_4 (Activation) (None, 12, 12, 64) 0
------------------------------
max_pooling2d_4 (MaxPooling2 (None, 6, 6, 64) 0
------------------------------
conv2d_5 (Conv2D) (None, 6, 6, 128) 73856
------------------------------
activation_5 (Activation) (None, 6, 6, 128) 0
------------------------------
max_pooling2d_5 (MaxPooling2 (None, 3, 3, 128) 0
------------------------------
conv2d_6 (Conv2D) (None, 3, 3, 128) 147584
------------------------------
activation_6 (Activation) (None, 3, 3, 128) 0
------------------------------
max_pooling2d_6 (MaxPooling2 (None, 1, 1, 128) 0
------------------------------
flatten_1 (Flatten) (None, 128) 0
------------------------------
dropout_1 (Dropout) (None, 128) 0
------------------------------
dense_1 (Dense) (None, 1024) 132096
------------------------------
dense_2 (Dense) (None, 256) 262400
------------------------------
dense_3 (Dense) (None, 64) 16448
------------------------------
dense_4 (Dense) (None, 1) 65
Total params: 697,441
Trainable params: 697,441
Non-trainable params: 0
------------------------------
Process finished with exit code 0
`
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Everything is tested with the v2 files. The angle is still static. Please note the remarkable difference between these two models I posted above. If I use the model .h5 shipped in this repo everything works fine. But my own trained fails. |
Yes true. I just realised the new model trained is only 8.258 mb whereas
the real model is 28.89 mb. Something wrong somewhere
…On Fri, Nov 22, 2019, 8:04 PM maxmstrmn ***@***.***> wrote:
Everything is tested with the v2 files. The angle is still static. Please
note the remarkable difference between these two models I posted above.
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However, I have tested with own dataset and the steering angle is moving.
It's weird but working
…On Fri, Nov 22, 2019, 10:16 PM Sriram Ramasamy ***@***.***> wrote:
Yes true. I just realised the new model trained is only 8.258 mb whereas
the real model is 28.89 mb. Something wrong somewhere
On Fri, Nov 22, 2019, 8:04 PM maxmstrmn ***@***.***> wrote:
> Everything is tested with the v2 files. The angle is still static. Please
> note the remarkable difference between these two models I posted above.
>
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hello i am getting an error while running code |
could you please share the whole code for AutopilotV2.py. |
The run.mp4 for v2 is not uploaded due to copyright issues. |
No description provided.
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