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Collecting pil
  Could not find a version that satisfies the requirement pil (from versions: )
No matching distribution found for pil
You are using pip version 8.1.1, however version 9.0.1 is available.
You should consider upgrading via the 'pip install --upgrade pip' command.

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import numpy as np
import pandas as pd
import os

import matplotlib.pyplot as plt
import skimage.feature
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import LabelBinarizer
import keras
from keras.models import Sequential, load_model
from keras.layers import Dense, Dropout, Activation, Flatten, Conv2D, MaxPooling2D, Lambda, Cropping2D
from keras.utils import np_utils

from collections import Counter

%matplotlib inline


    

    




Using Theano backend.

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class_names = ['adult_females', 'adult_males', 'juveniles', 'pups', 'subadult_males']

file_names = os.listdir("/Users/rcphillips/Documents/seal_the_deal/src/data/TrainSmall2/")
file_names = sorted(file_names, key=lambda 
                    item: (int(item.partition('.')[0]) if item[0].isdigit() else float('inf'), item)) 

# select a subset of files to run on
file_names = file_names[0:1]

# dataframe to store results in
coordinates_df = pd.DataFrame(index=file_names, columns=class_names)


    

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for filename in file_names:
    
    # read the Train and Train Dotted images
    image_1 = cv2.imread("../input/TrainDotted/" + filename)
    image_2 = cv2.imread("../input/Train/" + filename)
    
    cut = np.copy(image_2)
    
    # absolute difference between Train and Train Dotted
    image_3 = cv2.absdiff(image_1,image_2)
    
    # mask out blackened regions from Train Dotted
    mask_1 = cv2.cvtColor(image_1, cv2.COLOR_BGR2GRAY)
    mask_1[mask_1 < 20] = 0
    mask_1[mask_1 > 0] = 255
    
    mask_2 = cv2.cvtColor(image_2, cv2.COLOR_BGR2GRAY)
    mask_2[mask_2 < 20] = 0
    mask_2[mask_2 > 0] = 255
    
    image_3 = cv2.bitwise_or(image_3, image_3, mask=mask_1)
    image_3 = cv2.bitwise_or(image_3, image_3, mask=mask_2) 
    
    # convert to grayscale to be accepted by skimage.feature.blob_log
    image_3 = cv2.cvtColor(image_3, cv2.COLOR_BGR2GRAY)
    
    # detect blobs
    blobs = skimage.feature.blob_log(image_3, min_sigma=3, max_sigma=4, num_sigma=1, threshold=0.02)
    
    adult_males = []
    subadult_males = []
    pups = []
    juveniles = []
    adult_females = [] 
    
    image_circles = image_1
    
    for blob in blobs:
        # get the coordinates for each blob
        y, x, s = blob
        # get the color of the pixel from Train Dotted in the center of the blob
        g,b,r = image_1[int(y)][int(x)][:]
        
        # decision tree to pick the class of the blob by looking at the color in Train Dotted
        if r > 200 and g < 50 and b < 50: # RED
            adult_males.append((int(x),int(y)))
            cv2.circle(image_circles, (int(x),int(y)), 20, (0,0,255), 10) 
        elif r > 200 and g > 200 and b < 50: # MAGENTA
            subadult_males.append((int(x),int(y))) 
            cv2.circle(image_circles, (int(x),int(y)), 20, (250,10,250), 10)
        elif r < 100 and g < 100 and 150 < b < 200: # GREEN
            pups.append((int(x),int(y)))
            cv2.circle(image_circles, (int(x),int(y)), 20, (20,180,35), 10)
        elif r < 100 and  100 < g and b < 100: # BLUE
            juveniles.append((int(x),int(y))) 
            cv2.circle(image_circles, (int(x),int(y)), 20, (180,60,30), 10)
        elif r < 150 and g < 50 and b < 100:  # BROWN
            adult_females.append((int(x),int(y)))
            cv2.circle(image_circles, (int(x),int(y)), 20, (0,42,84), 10)  
            
        cv2.rectangle(cut, (int(x)-112,int(y)-112),(int(x)+112,int(y)+112), 0,-1)
            
    coordinates_df["adult_males"][filename] = adult_males
    coordinates_df["subadult_males"][filename] = subadult_males
    coordinates_df["adult_females"][filename] = adult_females
    coordinates_df["juveniles"][filename] = juveniles
    coordinates_df["pups"][filename] = pups


    

    




---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-26-3fa9fc944de9> in <module>()
      2 
      3     # read the Train and Train Dotted images
----> 4     image_1 = cv2.imread("../input/TrainDotted/" + filename)
      5     image_2 = cv2.imread("../input/Train/" + filename)
      6 

NameError: name 'cv2' is not defined

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'/Users/rcphillips/Documents/seal_the_deal'

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