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#--------------------------
# USER-SPECIFIED DATA
#--------------------------

# Tune these parameters

num_classes = 2
image_shape = (160, 576)
EPOCHS = 40
BATCH_SIZE = 16

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#--------------------------
# USER-SPECIFIED DATA
#--------------------------

# Tune these parameters

num_classes = 2
image_shape = (160, 576)
EPOCHS = 40
BATCH_SIZE = 16

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X = np.array([[0.0], [1.0], [2.0], [3.0]])
y = np.array([0.0, 2.0, 4.0, 6.0])

model_parameters = {'b': 0.0, 'w': np.array([0.5])}
y_predicted = [predict(x, model_parameters) for x in X]

plt.figure(figsize=(8, 5))
plt.yticks(np.arange(0, 7, 0.5))
plt.xticks(np.arange(0, 4, 1))
plt.ylabel("y")

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import cv2
import numpy as np

cap = cv2.VideoCapture('vtest.avi')
frame_width = int( cap.get(cv2.CAP_PROP_FRAME_WIDTH))

frame_height =int( cap.get( cv2.CAP_PROP_FRAME_HEIGHT))

fourcc = cv2.VideoWriter_fourcc('X','V','I','D')

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BYOB: Build Your Own Backend

MADCON 2017 Talk

Table of Contents

• Prerequisites
• Step 0: Setup
• Step 1: Express Yourself
• Step 2: Model Schemas
• Step 3: Building Models
• Step 4: Build Your Routes