Read in a dictionary-based file (like a JS output) that is saved as plaintext.

readdict.py

myfile = 'pred.js'
with open(myfile,'r') as inf:
    dict_from_file = eval(inf.read())

# each entry will be a dictionary, parse them as you wish.
print('keys', dict_from_file[0].keys()) # will list available key-value pairs.

# I'm going to extract the data that I personally care about. Class labels.
# playing with these lines allowed me to find the numbers representing the class labels
print(dict_from_file[0]['predicted'][3])
print(dict_from_file[0]['image_path'][42])

# we will store the info in some lists.
true_class = []
pred_class = []

# this is based on how I use folder names and file names to save test images... 
# also how predictions are saved using this python project: https://github.com/matthew-sochor/transfer
for D in dict_from_file:
  pred_class.append(int(D['predicted'][3]))
  true_class.append(int(D['image_path'][42]))
  
# lets gauge our accuracy
sum([pred_class[i] == true_class[i] for i in range(len(true_class))])