Issues importing my own dataset

[ben-coo-per]

I have been troubleshooting this for a few days now and I think it's about time to ask.
I have tried importing a couple of datasets that I reshaped with PIL to 96x96(RGB).

When I use one of the datasets and specify the input_height and output_height flags i get this error:

....DCGAN-tensorflow-master/utils.py", line 104, in transform
im = Image.fromarray(image[j:j+crop_h, i:i+crop_w])
NameError: name 'j' is not defined

When I specify the --crop flag I get this:

....DCGAN-tensorflow-master/utils.py", line 94, in center_crop
im = Image.fromarray(x[j:j+crop_h, i:i+crop_w])
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/PIL/Image.py", line 2517, in fromarray
raise TypeError("Cannot handle this data type")
TypeError: Cannot handle this data type

With all this being said, I think it is an issue with my images and the crop function. I have used the mnist dataset and it works fine.

For reference on what my images are, I have attached two.
If you have any advice on what I can change to fix this issue I would really appreciate it.

[wflaschka]

I just ran into the same issue and looked into the code.

It looks like the errors are caused by using the --crop argument on the commandline, which activates some wonky resizing / transforming / cropping logic in utils.py. However, if you do not use --crop, then you still get an error due to undefined values for i, j, etc in line 104.

Since all my images are already sized, cropped, and share a consistent colorspace, I simply skipped the wonky code by commenting lines 43-44 in utils.py:

  return transform(image, input_height, input_width,
                   resize_height, resize_width, crop)

And substituting with:

return image

Everything appears to be working smoothly now and my model is fitting. Give it a shot?

[ben-coo-per]

It looks like that worked. Thank you for your help!

[MyLovePoppet]

changed the code became a new error...

[] Reading checkpoints... ./out\20191014.164103 - data - faces - x108.z100.uniform_signed.y64.b64\checkpoint
[] Failed to find a checkpoint
[!] Load failed...
Traceback (most recent call last):
File "main.py", line 147, in
tf.app.run()
File "D:\Anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\platform\app.py", line 40, in run
_run(main=main, argv=argv, flags_parser=_parse_flags_tolerate_undef)
File "D:\Anaconda\envs\tensorflow\lib\site-packages\absl\app.py", line 299, in run
_run_main(main, args)
File "D:\Anaconda\envs\tensorflow\lib\site-packages\absl\app.py", line 250, in _run_main
sys.exit(main(argv))
File "main.py", line 120, in main
dcgan.train(FLAGS)
File "H:\2019Summer\代码\DCGAN\DCGAN-tensorflow-master\model.py", line 279, in train
feed_dict={ self.inputs: batch_images, self.z: batch_z })
File "D:\Anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\client\session.py", line 950, in run
run_metadata_ptr)
File "D:\Anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\client\session.py", line 1149, in _run
str(subfeed_t.get_shape())))
ValueError: Cannot feed value of shape (64, 96, 96, 3) for Tensor 'real_images:0', which has shape '(64, 64, 64, 3)'

[taotaoyuhust]

是utils.py 文件中的imread函数导致的问题，最后return的时候转换成了float，crop的时候Image.fromarray这句就会报错，
可将imread的返回改为return img_rgb
或在后面转成uint8

[taotaoyuhust]

另外，transform函数中有严重的bug
crop为true的时候，return还是返回的im

[Jumpleoleoleo]

changed the code became a new error...

[] Reading checkpoints... ./out\20191014.164103 - data - faces - x108.z100.uniform_signed.y64.b64\checkpoint [] Failed to find a checkpoint
[!] Load failed...
Traceback (most recent call last):
File "main.py", line 147, in
tf.app.run()
File "D:\Anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\platform\app.py", line 40, in run
_run(main=main, argv=argv, flags_parser=_parse_flags_tolerate_undef)
File "D:\Anaconda\envs\tensorflow\lib\site-packages\absl\app.py", line 299, in run
_run_main(main, args)
File "D:\Anaconda\envs\tensorflow\lib\site-packages\absl\app.py", line 250, in _run_main
sys.exit(main(argv))
File "main.py", line 120, in main
dcgan.train(FLAGS)
File "H:\2019Summer\代码\DCGAN\DCGAN-tensorflow-master\model.py", line 279, in train
feed_dict={ self.inputs: batch_images, self.z: batch_z })
File "D:\Anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\client\session.py", line 950, in run
run_metadata_ptr)
File "D:\Anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\client\session.py", line 1149, in _run
str(subfeed_t.get_shape())))
ValueError: Cannot feed value of shape (64, 96, 96, 3) for Tensor 'real_images:0', which has shape '(64, 64, 64, 3)'

Same problem!
Have you solved this problem?

[MyLovePoppet]

changed the code became a new error...
[] Reading checkpoints... ./out\20191014.164103 - data - faces - x108.z100.uniform_signed.y64.b64\checkpoint [] Failed to find a checkpoint
[!] Load failed...
Traceback (most recent call last):
File "main.py", line 147, in
tf.app.run()
File "D:\Anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\platform\app.py", line 40, in run
_run(main=main, argv=argv, flags_parser=_parse_flags_tolerate_undef)
File "D:\Anaconda\envs\tensorflow\lib\site-packages\absl\app.py", line 299, in run
_run_main(main, args)
File "D:\Anaconda\envs\tensorflow\lib\site-packages\absl\app.py", line 250, in _run_main
sys.exit(main(argv))
File "main.py", line 120, in main
dcgan.train(FLAGS)
File "H:\2019Summer\代码\DCGAN\DCGAN-tensorflow-master\model.py", line 279, in train
feed_dict={ self.inputs: batch_images, self.z: batch_z })
File "D:\Anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\client\session.py", line 950, in run
run_metadata_ptr)
File "D:\Anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\client\session.py", line 1149, in _run
str(subfeed_t.get_shape())))
ValueError: Cannot feed value of shape (64, 96, 96, 3) for Tensor 'real_images:0', which has shape '(64, 64, 64, 3)'

Same problem!
Have you solved this problem?

Yes, from zhihu link "https://zhuanlan.zhihu.com/p/24767059" the @igoindown ’s comment，

His solution is working for me:

我运行过程中一共遇到了4个问题：

1:TypeError: Cannot handle this data type

跟着代码一步步crtl+b进utils.py把94行改为：

im = Image.fromarray(np.uint8(x[j:j+crop_h, i:i+crop_w]))

2:再run； 95行会报错 data type not understood

把95行改为：return np.array(im.resize([resize_h, resize_w]), np.uint8(Image.BILINEAR))

3:再运行会提示resize_h没有定义。这里不知道是不是bug。我整个把97行的transform函数改为如下：

def transform(image, input_height, input_width,
resize_height=64, resize_width=64, crop=True):
if crop:
cropped_image = center_crop(
image, input_height, input_width,
resize_height, resize_width)
h, w = image.shape[:2]
j = int(round((h - input_height) / 2.))
i = int(round((w - input_width) / 2.))
im = Image.fromarray(np.uint8(image[j:j + input_height, i:i + input_width]))
else:
im = Image.fromarray(image[j:j+crop_h, i:i+crop_w])
return np.array(im.resize([resize_height, resize_width]), np.uint8(Image.BILINEAR))/127.5 - 1.

4：此时函数已经可以正常运行了，但是不能存图。

原因：utils.py中 scipy.misc.imsave被弃用

添加imageio库。用imageio.imwrite代替

大功告成！

translate version:

1:TypeError: Cannot handle this data type

Follow the code step by step crtl+b into utils.py to change line 94 to:

Im = Image.fromarray(np.uint8(x[j:j+crop_h, i:i+crop_w]))

2: Run again; 95 lines will report error data type not understood

Change line 95 to: return np.array(im.resize([resize_h, resize_w]), np.uint8(Image.BILINEAR))

3: Re-run will prompt resize_h is not defined. I don't know if it is a bug here. I changed the 97-line transform function to the following:

Def transform(image, input_height, input_width,
Resize_height=64, resize_width=64, crop=True):
If crop:
Cropped_image = center_crop(
Image, input_height, input_width,
Resize_height, resize_width)
h, w = image.shape[:2]
j = int(round((h - input_height) / 2.))
i = int(round((w - input_width) / 2.))
Im = Image.fromarray(np.uint8(image[j:j + input_height, i:i + input_width]))
Else:
Im = Image.fromarray(image[j:j+crop_h, i:i+crop_w])
Return np.array(im.resize([resize_height, resize_width]), np.uint8(Image.BILINEAR))/127.5 - 1.

4: The function is now ready to run, but it cannot be saved.

Cause: scipy.misc.imsave is deprecated in utils.py

Add the imageio library. Replace with imageio.imwrite

You're done!

[Jumpleoleoleo]

changed the code became a new error...
[] Reading checkpoints... ./out\20191014.164103 - data - faces - x108.z100.uniform_signed.y64.b64\checkpoint [] Failed to find a checkpoint
[!] Load failed...
Traceback (most recent call last):
File "main.py", line 147, in
tf.app.run()
File "D:\Anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\platform\app.py", line 40, in run
_run(main=main, argv=argv, flags_parser=_parse_flags_tolerate_undef)
File "D:\Anaconda\envs\tensorflow\lib\site-packages\absl\app.py", line 299, in run
_run_main(main, args)
File "D:\Anaconda\envs\tensorflow\lib\site-packages\absl\app.py", line 250, in _run_main
sys.exit(main(argv))
File "main.py", line 120, in main
dcgan.train(FLAGS)
File "H:\2019Summer\代码\DCGAN\DCGAN-tensorflow-master\model.py", line 279, in train
feed_dict={ self.inputs: batch_images, self.z: batch_z })
File "D:\Anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\client\session.py", line 950, in run
run_metadata_ptr)
File "D:\Anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\client\session.py", line 1149, in _run
str(subfeed_t.get_shape())))
ValueError: Cannot feed value of shape (64, 96, 96, 3) for Tensor 'real_images:0', which has shape '(64, 64, 64, 3)'

Same problem!
Have you solved this problem?

Yes, from zhihu link "https://zhuanlan.zhihu.com/p/24767059" the @igoindown ’s comment，

His solution is working for me:

我运行过程中一共遇到了4个问题：

1:TypeError: Cannot handle this data type

跟着代码一步步crtl+b进utils.py把94行改为：

im = Image.fromarray(np.uint8(x[j:j+crop_h, i:i+crop_w]))

2:再run； 95行会报错 data type not understood

把95行改为：return np.array(im.resize([resize_h, resize_w]), np.uint8(Image.BILINEAR))

3:再运行会提示resize_h没有定义。这里不知道是不是bug。我整个把97行的transform函数改为如下：

def transform(image, input_height, input_width,
resize_height=64, resize_width=64, crop=True):
if crop:
cropped_image = center_crop(
image, input_height, input_width,
resize_height, resize_width)
h, w = image.shape[:2]
j = int(round((h - input_height) / 2.))
i = int(round((w - input_width) / 2.))
im = Image.fromarray(np.uint8(image[j:j + input_height, i:i + input_width]))
else:
im = Image.fromarray(image[j:j+crop_h, i:i+crop_w])
return np.array(im.resize([resize_height, resize_width]), np.uint8(Image.BILINEAR))/127.5 - 1.

4：此时函数已经可以正常运行了，但是不能存图。

原因：utils.py中 scipy.misc.imsave被弃用

添加imageio库。用imageio.imwrite代替

大功告成！

translate version:

1:TypeError: Cannot handle this data type

Follow the code step by step crtl+b into utils.py to change line 94 to:

Im = Image.fromarray(np.uint8(x[j:j+crop_h, i:i+crop_w]))

2: Run again; 95 lines will report error data type not understood

Change line 95 to: return np.array(im.resize([resize_h, resize_w]), np.uint8(Image.BILINEAR))

3: Re-run will prompt resize_h is not defined. I don't know if it is a bug here. I changed the 97-line transform function to the following:

Def transform(image, input_height, input_width,
Resize_height=64, resize_width=64, crop=True):
If crop:
Cropped_image = center_crop(
Image, input_height, input_width,
Resize_height, resize_width)
h, w = image.shape[:2]
j = int(round((h - input_height) / 2.))
i = int(round((w - input_width) / 2.))
Im = Image.fromarray(np.uint8(image[j:j + input_height, i:i + input_width]))
Else:
Im = Image.fromarray(image[j:j+crop_h, i:i+crop_w])
Return np.array(im.resize([resize_height, resize_width]), np.uint8(Image.BILINEAR))/127.5 - 1.

4: The function is now ready to run, but it cannot be saved.

Cause: scipy.misc.imsave is deprecated in utils.py

Add the imageio library. Replace with imageio.imwrite

You're done!

Thank U soooo much for your help!!!

[xk88372527]

changed the code became a new error...
[] Reading checkpoints... ./out\20191014.164103 - data - faces - x108.z100.uniform_signed.y64.b64\checkpoint [] Failed to find a checkpoint [!] Load failed... Traceback (most recent call last): File "main.py", line 147, in tf.app.run() File "D:\Anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\platform\app.py", line 40, in run _run(main=main, argv=argv, flags_parser=_parse_flags_tolerate_undef) File "D:\Anaconda\envs\tensorflow\lib\site-packages\absl\app.py", line 299, in run _run_main(main, args) File "D:\Anaconda\envs\tensorflow\lib\site-packages\absl\app.py", line 250, in _run_main sys.exit(main(argv)) File "main.py", line 120, in main dcgan.train(FLAGS) File "H:\2019Summer\代码\DCGAN\DCGAN-tensorflow-master\model.py", line 279, in train feed_dict={ self.inputs: batch_images, self.z: batch_z }) File "D:\Anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\client\session.py", line 950, in run run_metadata_ptr) File "D:\Anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\client\session.py", line 1149, in _run str(subfeed_t.get_shape()))) ValueError: Cannot feed value of shape (64, 96, 96, 3) for Tensor 'real_images:0', which has shape '(64, 64, 64, 3)'

Same problem! Have you solved this problem?

Yes, from zhihu link "https://zhuanlan.zhihu.com/p/24767059" the @igoindown ’s comment，

His solution is working for me:

我运行过程中一共遇到了4个问题：

1:TypeError: Cannot handle this data type

跟着代码一步步crtl+b进utils.py把94行改为：

im = Image.fromarray(np.uint8(x[j:j+crop_h, i:i+crop_w]))

2:再run； 95行会报错 data type not understood

把95行改为：return np.array(im.resize([resize_h, resize_w]), np.uint8(Image.BILINEAR))

3:再运行会提示resize_h没有定义。这里不知道是不是bug。我整个把97行的transform函数改为如下：

def transform(image, input_height, input_width,
resize_height=64, resize_width=64, crop=True):
if crop:
cropped_image = center_crop(
image, input_height, input_width,
resize_height, resize_width)
h, w = image.shape[:2]
j = int(round((h - input_height) / 2.))
i = int(round((w - input_width) / 2.))
im = Image.fromarray(np.uint8(image[j:j + input_height, i:i + input_width]))
else:
im = Image.fromarray(image[j:j+crop_h, i:i+crop_w])
return np.array(im.resize([resize_height, resize_width]), np.uint8(Image.BILINEAR))/127.5 - 1.

4：此时函数已经可以正常运行了，但是不能存图。

原因：utils.py中 scipy.misc.imsave被弃用

添加imageio库。用imageio.imwrite代替

大功告成！

translate version:

1:TypeError: Cannot handle this data type

Follow the code step by step crtl+b into utils.py to change line 94 to:

Im = Image.fromarray(np.uint8(x[j:j+crop_h, i:i+crop_w]))

2: Run again; 95 lines will report error data type not understood

Change line 95 to: return np.array(im.resize([resize_h, resize_w]), np.uint8(Image.BILINEAR))

3: Re-run will prompt resize_h is not defined. I don't know if it is a bug here. I changed the 97-line transform function to the following:

Def transform(image, input_height, input_width,
Resize_height=64, resize_width=64, crop=True):
If crop:
Cropped_image = center_crop(
Image, input_height, input_width,
Resize_height, resize_width)
h, w = image.shape[:2]
j = int(round((h - input_height) / 2.))
i = int(round((w - input_width) / 2.))
Im = Image.fromarray(np.uint8(image[j:j + input_height, i:i + input_width]))
Else:
Im = Image.fromarray(image[j:j+crop_h, i:i+crop_w])
Return np.array(im.resize([resize_height, resize_width]), np.uint8(Image.BILINEAR))/127.5 - 1.

4: The function is now ready to run, but it cannot be saved.

Cause: scipy.misc.imsave is deprecated in utils.py

Add the imageio library. Replace with imageio.imwrite

You're done!

thank you!
The function is run,But there is a warning as follows:
"Lossy conversion from float64 to uint8. Range [0, 1]. Convert image to uint8 prior to saving to suppress this warning."
Will this affect the running of the program?

[George-078]

changed the code became a new error...
[] Reading checkpoints... ./out\20191014.164103 - data - faces - x108.z100.uniform_signed.y64.b64\checkpoint [] Failed to find a checkpoint
[!] Load failed...
Traceback (most recent call last):
File "main.py", line 147, in
tf.app.run()
File "D:\Anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\platform\app.py", line 40, in run
_run(main=main, argv=argv, flags_parser=_parse_flags_tolerate_undef)
File "D:\Anaconda\envs\tensorflow\lib\site-packages\absl\app.py", line 299, in run
_run_main(main, args)
File "D:\Anaconda\envs\tensorflow\lib\site-packages\absl\app.py", line 250, in _run_main
sys.exit(main(argv))
File "main.py", line 120, in main
dcgan.train(FLAGS)
File "H:\2019Summer\代码\DCGAN\DCGAN-tensorflow-master\model.py", line 279, in train
feed_dict={ self.inputs: batch_images, self.z: batch_z })
File "D:\Anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\client\session.py", line 950, in run
run_metadata_ptr)
File "D:\Anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\client\session.py", line 1149, in _run
str(subfeed_t.get_shape())))
ValueError: Cannot feed value of shape (64, 96, 96, 3) for Tensor 'real_images:0', which has shape '(64, 64, 64, 3)'

Same problem!
Have you solved this problem?

Yes, from zhihu link "https://zhuanlan.zhihu.com/p/24767059" the @igoindown ’s comment，

His solution is working for me:

我运行过程中一共遇到了4个问题：

1:TypeError: Cannot handle this data type

跟着代码一步步crtl+b进utils.py把94行改为：

im = Image.fromarray(np.uint8(x[j:j+crop_h, i:i+crop_w]))

2:再run； 95行会报错 data type not understood

把95行改为：return np.array(im.resize([resize_h, resize_w]), np.uint8(Image.BILINEAR))

3:再运行会提示resize_h没有定义。这里不知道是不是bug。我整个把97行的transform函数改为如下：

def transform(image, input_height, input_width,
resize_height=64, resize_width=64, crop=True):
if crop:
cropped_image = center_crop(
image, input_height, input_width,
resize_height, resize_width)
h, w = image.shape[:2]
j = int(round((h - input_height) / 2.))
i = int(round((w - input_width) / 2.))
im = Image.fromarray(np.uint8(image[j:j + input_height, i:i + input_width]))
else:
im = Image.fromarray(image[j:j+crop_h, i:i+crop_w])
return np.array(im.resize([resize_height, resize_width]), np.uint8(Image.BILINEAR))/127.5 - 1.

4：此时函数已经可以正常运行了，但是不能存图。

原因：utils.py中 scipy.misc.imsave被弃用

添加imageio库。用imageio.imwrite代替

大功告成！

translate version:

1:TypeError: Cannot handle this data type

Follow the code step by step crtl+b into utils.py to change line 94 to:

Im = Image.fromarray(np.uint8(x[j:j+crop_h, i:i+crop_w]))

2: Run again; 95 lines will report error data type not understood

Change line 95 to: return np.array(im.resize([resize_h, resize_w]), np.uint8(Image.BILINEAR))

3: Re-run will prompt resize_h is not defined. I don't know if it is a bug here. I changed the 97-line transform function to the following:

Def transform(image, input_height, input_width,
Resize_height=64, resize_width=64, crop=True):
If crop:
Cropped_image = center_crop(
Image, input_height, input_width,
Resize_height, resize_width)
h, w = image.shape[:2]
j = int(round((h - input_height) / 2.))
i = int(round((w - input_width) / 2.))
Im = Image.fromarray(np.uint8(image[j:j + input_height, i:i + input_width]))
Else:
Im = Image.fromarray(image[j:j+crop_h, i:i+crop_w])
Return np.array(im.resize([resize_height, resize_width]), np.uint8(Image.BILINEAR))/127.5 - 1.

4: The function is now ready to run, but it cannot be saved.

Cause: scipy.misc.imsave is deprecated in utils.py

Add the imageio library. Replace with imageio.imwrite

You're done!

你好，我根据你的修改了transform，还是会显示j，j+crop_h,i,i+crop_w未被定义，请问是什么原因呢