TypeError: 'dict_keys' object does not support indexing

[HARIHARAN1103]

I tired demo.ipynb at google colab. After installing the requirements I started to run the code. There arise an issue in the follwing code,

heatmap_avg = np.zeros((oriImg.shape[0], oriImg.shape[1], 19))
paf_avg = np.zeros((oriImg.shape[0], oriImg.shape[1], 38))

first figure shows padded images

f, axarr = plt.subplots(1, len(multiplier))
f.set_size_inches((20, 5))

second figure shows heatmaps

f2, axarr2 = plt.subplots(1, len(multiplier))
f2.set_size_inches((20, 5))

third figure shows PAFs

f3, axarr3 = plt.subplots(2, len(multiplier))
f3.set_size_inches((20, 10))

for m in range(len(multiplier)):
scale = multiplier[m]
imageToTest = cv.resize(oriImg, (0,0), fx=scale, fy=scale, interpolation=cv.INTER_CUBIC)
imageToTest_padded, pad = util.padRightDownCorner(imageToTest, model['stride'], model['padValue'])
print(imageToTest_padded.shape)

axarr[m].imshow(imageToTest_padded[:,:,[2,1,0]])
axarr[m].set_title('Input image: scale %d' % m)

net.blobs['data'].reshape(*(1, 3, imageToTest_padded.shape[0], imageToTest_padded.shape[1]))
#net.forward() # dry run
net.blobs['data'].data[...] = np.transpose(np.float32(imageToTest_padded[:,:,:,np.newaxis]), (3,2,0,1))/256 - 0.5;
start_time = time.time()
output_blobs = net.forward()
print('At scale %d, The CNN took %.2f ms.' % (m, 1000 * (time.time() - start_time)))

# extract outputs, resize, and remove padding
heatmap = np.transpose(np.squeeze(net.blobs[output_blobs.keys()[1]].data), (1,2,0)) # output 1 is heatmaps
heatmap = cv.resize(heatmap, (0,0), fx=model['stride'], fy=model['stride'], interpolation=cv.INTER_CUBIC)
heatmap = heatmap[:imageToTest_padded.shape[0]-pad[2], :imageToTest_padded.shape[1]-pad[3], :]
heatmap = cv.resize(heatmap, (oriImg.shape[1], oriImg.shape[0]), interpolation=cv.INTER_CUBIC)

paf = np.transpose(np.squeeze(net.blobs[output_blobs.keys()[0]].data), (1,2,0)) # output 0 is PAFs
paf = cv.resize(paf, (0,0), fx=model['stride'], fy=model['stride'], interpolation=cv.INTER_CUBIC)
paf = paf[:imageToTest_padded.shape[0]-pad[2], :imageToTest_padded.shape[1]-pad[3], :]
paf = cv.resize(paf, (oriImg.shape[1], oriImg.shape[0]), interpolation=cv.INTER_CUBIC)

# visualization
axarr2[m].imshow(oriImg[:,:,[2,1,0]])
ax2 = axarr2[m].imshow(heatmap[:,:,3], alpha=.5) # right wrist
axarr2[m].set_title('Heatmaps (Rwri): scale %d' % m)

axarr3.flat[m].imshow(oriImg[:,:,[2,1,0]])
ax3x = axarr3.flat[m].imshow(paf[:,:,16], alpha=.5) # right elbow
axarr3.flat[m].set_title('PAFs (x comp. of Rwri to Relb): scale %d' % m)
axarr3.flat[len(multiplier) + m].imshow(oriImg[:,:,[2,1,0]])
ax3y = axarr3.flat[len(multiplier) + m].imshow(paf[:,:,17], alpha=.5) # right wrist
axarr3.flat[len(multiplier) + m].set_title('PAFs (y comp. of Relb to Rwri): scale %d' % m)

heatmap_avg = heatmap_avg + heatmap / len(multiplier)
paf_avg = paf_avg + paf / len(multiplier)

f2.subplots_adjust(right=0.93)
cbar_ax = f2.add_axes([0.95, 0.15, 0.01, 0.7])
_ = f2.colorbar(ax2, cax=cbar_ax)

f3.subplots_adjust(right=0.93)
cbar_axx = f3.add_axes([0.95, 0.57, 0.01, 0.3])
_ = f3.colorbar(ax3x, cax=cbar_axx)
cbar_axy = f3.add_axes([0.95, 0.15, 0.01, 0.3])
_ = f3.colorbar(ax3y, cax=cbar_axy)

After excuting the code,

(184, 200, 3)
At scale 0, The CNN took 105.94 ms.

TypeError Traceback (most recent call last)
in ()
28
29 # extract outputs, resize, and remove padding
---> 30 heatmap = np.transpose(np.squeeze(net.blobs[output_blobs.keys()[1]].data), (1,2,0)) # output 1 is heatmaps
31 heatmap = cv.resize(heatmap, (0,0), fx=model['stride'], fy=model['stride'], interpolation=cv.INTER_CUBIC)
32 heatmap = heatmap[:imageToTest_padded.shape[0]-pad[2], :imageToTest_padded.shape[1]-pad[3], :]

TypeError: 'dict_keys' object does not support indexing

[retro2old]

Hello,
I have the same problem.
I managed to get a bit further by doing
tmp = output_blobs.keys()
print(tmp)

and manually write the key

output_blobs is dictionary and cannot be indexed as written by the authors

heatmap = np.transpose(np.squeeze(net.blobs['Mconv7_stage_6_L1'].data), (1,2,0)) # output 1

But afterwards
heatmap and heatmap_avg
pft and pft_avg
Have dimension problems problems

[utisolichah]

how you solve the dimension problem after change ouput_blobs.keys()?

[ghost]

Are you running Python3? Then use list(dict.keys()). I think Python2 returned dict.keys() as a list, not Python3.