Vishnu Nandakumar Vishnunkumar

## arsenal-prem.csv

          
            date_col
            home
            away
            score
            points
            home-adv
            referee
            opponent
            PI

            
              2018-08-12
              arsenal
              manchester city
              0–2
              0
              1
              Michael Oliver
              manchestercity
              1.3102245221600866

            
              2018-08-18
              chelsea
              arsenal
              3–2
              0
              0
              Martin Atkinson
              chelsea
              1.095206298862087

            
              2018-08-25
              arsenal
              west ham united
              3–1
              3
              1
              Graham Scott
              westhamunited
              0.8275324819853656

            
              2018-09-02
              cardiff city
              arsenal
              2–3
              3
              0
              Anthony Taylor
              cardiffcity
              0.5715382689257991

            
              2018-09-15
              newcastle united
              arsenal
              1–2
              3
              0
              Lee Probert
              newcastleunited
              0.7149987480176946

            
              2018-09-23
              arsenal
              everton
              2–0
              3
              1
              Jonathan Moss
              everton
              0.8625768578026318

            
              2018-09-29
              arsenal
              watford
              2–0
              3
              1
              Anthony Taylor
              watford
              0.5499707870795425

            
              2018-10-07
              fulham
              arsenal
              1–5
              3
              0
              Paul Tierney
              fulham
              0.4290960687755612

            
              2018-10-22
              arsenal
              leicester city
              3–1
              3
              1
              Chris Kavanagh
              leicestercity
              0.9565589961884093

## arsenal-ref-home.tsv

          
            
            ds
            home-adv
            referee_Anthony Taylor
            referee_Jonathan Moss
            referee_Martin Atkinson
            referee_Michael Oliver
            referee_Mike Dean
            cum_pts_preds

            
              0
              2021-08-15
              0
              0
              0
              1
              0
              0
              0

            
              1
              2021-08-22
              1
              1
              0
              0
              0
              1
              1

            
              2
              2021-08-29
              0
              0
              1
              0
              0
              0
              4

            
              3
              2021-09-05
              1
              0
              0
              0
              1
              0
              5

            
              4
              2021-09-12
              1
              1
              0
              0
              0
              0
              6

## arsenal-home-info.tsv

          
            
            ds
            home-adv
            cum_pts_preds

            
              0
              2021-08-15
              0
              0

            
              1
              2021-08-22
              1
              0

            
              2
              2021-08-29
              0
              3

            
              3
              2021-09-05
              1
              7

            
              4
              2021-09-12
              1
              7

## arsenal-no-info.csv

          
            ds
            pts

            
              2021-08-15
              0

            
              2021-08-22
              0

            
              2021-08-29
              3

            
              2021-09-05
              6

            
              2021-09-12
              6

## keras_bert.py
from transformers import AutoTokenizer, TFAutoModelForSequenceClassification
import tensorflow as tf

model_name = 'bert-base-cased'
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = TFAutoModelForSequenceClassification.from_pretrained(model_name, num_labels=2)

texts = ["I'm a positive example!", "I'm a negative example!"]
labels = [1, 0]

## f1.html
<html>
<head><meta charset="utf-8" /></head>
<body>
    <div>                        <script type="text/javascript">window.PlotlyConfig = {MathJaxConfig: 'local'};</script>
        <script type="text/javascript">/**
* plotly.js v2.2.0
* Copyright 2012-2021, Plotly, Inc.
* All rights reserved.
* Licensed under the MIT license
*/

## processing.py
def pro_df(df, team):

  """
  Function to get the date, home-team, away-team, points, referee and score etc
  """
    df['date'] = [x[0] for x in df[0]]
    df['home'] = [x[1].lower() for x in df[0]]
    df['score'] = [x[2] for x in df[0]]
    df['away'] = [x[3].lower() for x in df[0]]
    df['referee'] = [(' ').join(x[4].split(' ')[-2:]) for x in df[1]]

## get_prediction.py
preds = model.predict(x_test)
col = []
aut = []
for i in range(0, preds[0].shape[0]):
col.append(np.argmax(preds[0][i]))
aut.append(np.argmax(preds[1][i]))
re_map1 = {}
for k, v in map_1.items():
re_map1[v] = k
re_map2 = {}

## test_data_prep.py
dir_2 = 'working/'
test_list = []
for file in os.listdir(dir_2):
    if file.split('.')[1] != 'ipynb':
        json_dict = {}
        img_arr = cv2.imread(os.path.join(dir_2, file))[...,::-1] #convert BGR to RGB format
        resized_arr = cv2.resize(img_arr, (img_size, img_size)) # Reshaping images to preferred size
        json_dict['image'] = resized_arr
        test_list.append(json_dict)
test = np.array(test_list)

## model_multi-task.py
inputs = tf.keras.layers.Input(shape=[128, 128, 3], name='main_input')
main_branch = hub.KerasLayer("https://tfhub.dev/google/imagenet/mobilenet_v2_075_128/classification/5")(inputs)
main_branch = tf.keras.layers.Flatten()(main_branch)
main_branch = tf.keras.layers.Dense(1024, activation='relu')(main_branch)
colour_branch = tf.keras.layers.Dense(c_1, activation='softmax', name='colour_output')(main_branch)
auto_branch = tf.keras.layers.Dense(c_2, activation='softmax', name='auto_output')(main_branch)
model = tf.keras.Model(inputs = inputs,
outputs = [colour_branch, auto_branch])

model.compile(optimizer='rmsprop',
date_col	home	away	score	points	home-adv	referee	opponent	PI
2018-08-12	arsenal	manchester city	0–2	0	1	Michael Oliver	manchestercity	1.3102245221600866
2018-08-18	chelsea	arsenal	3–2	0	0	Martin Atkinson	chelsea	1.095206298862087
2018-08-25	arsenal	west ham united	3–1	3	1	Graham Scott	westhamunited	0.8275324819853656
2018-09-02	cardiff city	arsenal	2–3	3	0	Anthony Taylor	cardiffcity	0.5715382689257991
2018-09-15	newcastle united	arsenal	1–2	3	0	Lee Probert	newcastleunited	0.7149987480176946
2018-09-23	arsenal	everton	2–0	3	1	Jonathan Moss	everton	0.8625768578026318
2018-09-29	arsenal	watford	2–0	3	1	Anthony Taylor	watford	0.5499707870795425
2018-10-07	fulham	arsenal	1–5	3	0	Paul Tierney	fulham	0.4290960687755612
2018-10-22	arsenal	leicester city	3–1	3	1	Chris Kavanagh	leicestercity	0.9565589961884093
	ds	home-adv	referee_Anthony Taylor	referee_Jonathan Moss	referee_Martin Atkinson	referee_Michael Oliver	referee_Mike Dean	cum_pts_preds
0	2021-08-15	0	0	0	1	0	0	0
1	2021-08-22	1	1	0	0	0	1	1
2	2021-08-29	0	0	1	0	0	0	4
3	2021-09-05	1	0	0	0	1	0	5
4	2021-09-12	1	1	0	0	0	0	6
	from transformers import AutoTokenizer, TFAutoModelForSequenceClassification
	import tensorflow as tf

	model_name = 'bert-base-cased'
	tokenizer = AutoTokenizer.from_pretrained(model_name)
	model = TFAutoModelForSequenceClassification.from_pretrained(model_name, num_labels=2)

	texts = ["I'm a positive example!", "I'm a negative example!"]
	labels = [1, 0]
	<html>
	<head><meta charset="utf-8" /></head>
	<body>
	<div> <script type="text/javascript">window.PlotlyConfig = {MathJaxConfig: 'local'};</script>
	<script type="text/javascript">/**
	* plotly.js v2.2.0
	* Copyright 2012-2021, Plotly, Inc.
	* All rights reserved.
	* Licensed under the MIT license
	*/
	def pro_df(df, team):

	"""
	Function to get the date, home-team, away-team, points, referee and score etc
	"""
	df['date'] = [x[0] for x in df[0]]
	df['home'] = [x[1].lower() for x in df[0]]
	df['score'] = [x[2] for x in df[0]]
	df['away'] = [x[3].lower() for x in df[0]]
	df['referee'] = [(' ').join(x[4].split(' ')[-2:]) for x in df[1]]
	preds = model.predict(x_test)
	col = []
	aut = []
	for i in range(0, preds[0].shape[0]):
	col.append(np.argmax(preds[0][i]))
	aut.append(np.argmax(preds[1][i]))
	re_map1 = {}
	for k, v in map_1.items():
	re_map1[v] = k
	re_map2 = {}
	dir_2 = 'working/'
	test_list = []
	for file in os.listdir(dir_2):
	if file.split('.')[1] != 'ipynb':
	json_dict = {}
	img_arr = cv2.imread(os.path.join(dir_2, file))[...,::-1] #convert BGR to RGB format
	resized_arr = cv2.resize(img_arr, (img_size, img_size)) # Reshaping images to preferred size
	json_dict['image'] = resized_arr
	test_list.append(json_dict)
	test = np.array(test_list)
	inputs = tf.keras.layers.Input(shape=[128, 128, 3], name='main_input')
	main_branch = hub.KerasLayer("https://tfhub.dev/google/imagenet/mobilenet_v2_075_128/classification/5")(inputs)
	main_branch = tf.keras.layers.Flatten()(main_branch)
	main_branch = tf.keras.layers.Dense(1024, activation='relu')(main_branch)
	colour_branch = tf.keras.layers.Dense(c_1, activation='softmax', name='colour_output')(main_branch)
	auto_branch = tf.keras.layers.Dense(c_2, activation='softmax', name='auto_output')(main_branch)
	model = tf.keras.Model(inputs = inputs,
	outputs = [colour_branch, auto_branch])

	model.compile(optimizer='rmsprop',