Santha Lakshmi Narayana santhalakshminarayana

Going ahead full throttle.

santhalakshminarayana / white_board_enhance.py

Created October 18, 2021 22:06

White Board image color enhancement in python

	import argparse
	import cv2
	import numpy as np

	def normalize_kernel(kernel, k_width, k_height, scaling_factor = 1.0):
	'''Zero-summing normalize kernel'''

	K_EPS = 1.0e-12
	# positive and negative sum of kernel values
	pos_range, neg_range = 0, 0

santhalakshminarayana / Quotes_generation.py

Last active January 6, 2020 09:21

Quotes Generation - Medium

	def predict(x, temp):
	probs = F.softmax(x / temp, dim = 0)
	probs = np.squeeze(probs.detach().cpu().numpy())
	ind = np.random.choice(vocab_len, 1, p = probs)
	return ind[0]

	generated_text = ['there','is','no','one','love']
	curr_len = 0
	embeds = []
	is_end = word_to_int[';']

santhalakshminarayana / Quotes_LSTM_model.py

Last active November 4, 2020 20:05

Quotes LSTM model - Medium

	def get_batches_x(tot_seq, batch_size):
	ind = np.random.permutation(tot_seq).tolist()
	i = 0
	for i in range(0, tot_seq, batch_size):
	batch_ids = ind[i:i+batch_size]
	yield X[batch_ids], Y[batch_ids]

	class Quote_Generator(nn.Module):
	def __init__(self, embed_size, hidden_size, vocab_len):
	super(Quote_Generator, self).__init__()

santhalakshminarayana / Quotes_input_LSTM.py

Last active January 6, 2020 07:37

	window = 5 # max_seq_length
	sequences, next_words = [], []
	for quote in quotes:
	words = quote.split(' ')
	for i in range(0,len(words) - window + 1):
	sequences.append(words[i:i+window])
	if (i + window) < len(words):
	next_words.append(words[i+window])
	else:
	next_words.append(';')

santhalakshminarayana / Quotes_TSNE.py

Created January 6, 2020 07:20

Quotes TSNE - Medium

	tsne = TSNE(n_components=2, perplexity=40, n_iter=300,metric='cosine')
	n_points = 100
	emb_tsne = tsne.fit_transform(emb[:n_points, :])

	labels = list(word_to_int.keys())[:n_points]
	x = emb_tsne[:,0]
	y = emb_tsne[:,1]
	plt.figure(figsize=(16, 16))
	for i in range(n_points):
	plt.scatter(x[i],y[i])

santhalakshminarayana / Quotes_Glove_train.py

Created January 6, 2020 07:00

Quotes Glove Train - Medium

	def f_x(x, x_max, alpha):
	x = (x/x_max)**alpha
	return torch.min(x, torch.ones_like(x)).to(device)

	def weight_mse(w_x, x, log_x):
	loss = w_x * F.mse_loss(x, log_x, reduction='none')
	return torch.mean(loss).to(device)

	def glove_train(glove):
	epochs = 100

santhalakshminarayana / Quotes_Glove_model.py

Last active January 6, 2020 07:18

Quotes Glove Model - Medium

	def get_batch(batch_size):
	ind = np.random.permutation(occs.size).tolist()
	i = 0
	for i in range(0, tot_pairs, batch_size):
	batch_ids = ind[i:i+batch_size]
	yield p1[batch_ids], p2[batch_ids], occs[batch_ids]

	device = None
	if torch.cuda.is_available():
	device = torch.device("cuda:0")

santhalakshminarayana / Quotes_word_pairs.py

Created January 6, 2020 06:29

santhalakshminarayana / Quotes_similarity_score.py

Created January 6, 2020 06:17

Quotes Similarity Score - Medium

	co_occ_matrix = defaultdict(int)
	window = 5 # not greater than 5
	for sent in quotes:
	words = sent.split(' ')
	# first window
	for i in range(0, window):
	for j in range(i+1, window):
	weight = 1/(j-i)
	ind_1 = word_to_int[words[i]]
	ind_2 = word_to_int[words[j]]

santhalakshminarayana / Quotes_vocab_prep.py

Created January 6, 2020 06:05

Quotes Vocabulary Prep - Medium

	words_dict = dict()
	def unique_words(data_list):
	for x in data_list:
	for word in x.split(' '):
	words_dict[word] = 1
	return words_dict.keys()

	words = list(unique_words(quotes))
	words.sort()