View bounding_boxes.py
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import matplotlib.pyplot as plt | |
import matplotlib.patches as patches | |
image = plt.imread('index.jpg') | |
# draw emtpy figure | |
fig = plt.figure() | |
# define axis | |
ax = fig.add_axes([0, 0, 1, 1]) |
View backprop_convolv.py
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filter_update = [] | |
for i in range(f.shape[2]): | |
for j in range(f.shape[0]): | |
for k in range(f.shape[1]): | |
temp = 0 | |
spos_row = j | |
spos_col = k | |
epos_row = spos_row + s_row | |
epos_col = spos_col + s_col | |
for l in range(X.shape[2]): |
View data_info.py
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#loading data | |
import pandas as pd | |
data = pd.read_csv('train_LZdllcl.csv') | |
#data summary | |
data.info() |
View changing_dtype.py
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import pandas as pd | |
data = pd.read_csv('Train_SU63ISt.csv') | |
data['Datetime'] = pd.to_datetime(data['Datetime'],format='%d-%m-%Y %H:%M') | |
data.dtypes |
View building_kmeans.py
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#training k-means model | |
from sklearn.cluster import KMeans | |
kmeans = KMeans(n_clusters=4) | |
kmeans.fit(data) | |
#predictions from kmeans | |
pred = kmeans.predict(data) | |
frame = pd.DataFrame(data) | |
frame['cluster'] = pred | |
frame.columns = ['Weight', 'Height', 'cluster'] |
View feature_matching.py
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import cv2 | |
import matplotlib.pyplot as plt | |
%matplotlib inline | |
# read images | |
img1 = cv2.imread('eiffel_2.jpeg') | |
img2 = cv2.imread('eiffel_1.jpg') | |
img1 = cv2.cvtColor(img1, cv2.COLOR_BGR2GRAY) | |
img2 = cv2.cvtColor(img2, cv2.COLOR_BGR2GRAY) |
View adjust_gamma.py
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from skimage import exposure | |
#adjusting brightness | |
image = imread('images.jpeg') | |
image_bright = exposure.adjust_gamma(image, gamma=0.5,gain=1) | |
image_dark = exposure.adjust_gamma(image, gamma=1.5,gain=1) | |
# plotting images | |
plt.subplot(131), imshow(image) | |
plt.title('Original Image') |
View hog.py
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#creating hog features | |
fd, hog_image = hog(resized_img, orientations=9, pixels_per_cell=(8, 8), | |
cells_per_block=(2, 2), visualize=True, multichannel=True) |
View edge_features
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#importing the required libraries | |
import numpy as np | |
from skimage.io import imread, imshow | |
from skimage.filters import prewitt_h,prewitt_v | |
import matplotlib.pyplot as plt | |
%matplotlib inline | |
#reading the image | |
image = imread('puppy.jpeg',as_gray=True) |