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generate_image_data.py
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"""
Gera dataset inicial a partir de vídeos.
Giovanna Lima Marques
Ricardo Augusto Coelho
Tiago Goes Teles
Wellington de Jesus Albuquerque
Busca vídeos na pasta 'videos', onde deve haver uma pasta por palavra podendo conter vários vídeos por plavra.
Todas as saídas são feita na pasta output, cada vídeo é gerado uma pasta com todos os frames gerados para verificação.
O dataset está em um csv dentro da pasta output.
Algumas referências:
https://google.github.io/mediapipe/solutions/holistic.html
https://colab.research.google.com/drive/16UOYQ9hPM6L5tkq7oQBl1ULJ8xuK5Lae?usp=sharing#scrollTo=BAivyQOtFp
"""
import os
import cv2
import uuid
import math
import numpy as np
import pandas as pd
import mediapipe as mp
from pathlib import Path
import unicodedata
mp_drawing = mp.solutions.drawing_utils
mp_holistic = mp.solutions.holistic
WITH_Z = False
ignored = 0
DESIRED_HEIGHT = 200
DESIRED_WIDTH = 200
def process():
"""Processa todos os vídeos e salva o dataset"""
data = list()
words = [w for w in os.listdir("videos")] #Busca todas as palvras dentro da pasta 'videos'
words.sort()
for word in words:
wordFolder = os.path.join("videos", word)
wordVideos = [v for v in os.listdir(wordFolder)]
for wordVideo in wordVideos:
videoFile = os.path.join("videos", word, wordVideo)
data = data + processWord(word, videoFile)
saveData(data)
def processWord(word, video) -> list:
"""Processa um único vídeo de uma única palavra"""
global ignored
if (word == "0"):
word = "None"
data = list()
capture = cv2.VideoCapture(video)
output = os.path.abspath(os.path.join('./output', word))
output = output.replace('?', '').replace('.', '')
frame = 1
wordId = str(uuid.uuid4()) #Gera um identificador único para o vídeo
with mp_holistic.Holistic(static_image_mode=False, model_complexity=2, min_detection_confidence=0.45) as holistic:
while (cv2.waitKey(1) < 0): #Processa cada frame individualmente
conected, image = capture.read() #Ler um frame
if not conected:
cv2.waitKey()
break
h, w = image.shape[:2]
if h < w:
image = cv2.resize(image, (DESIRED_WIDTH, math.floor(h/(w/DESIRED_WIDTH))))
else:
image = cv2.resize(image, (math.floor(w/(h/DESIRED_HEIGHT)), DESIRED_HEIGHT))
#Obtem dados do vídeo e frame
fps = capture.get(cv2.CAP_PROP_FPS)
frame_count = capture.get(cv2.CAP_PROP_FRAME_COUNT)
duration = 0
if (fps != 0):
duration = frame_count / fps
time = frame / fps
image_width = image.shape[1]
image_height = image.shape[0]
#Prepara imagem para processo
image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
results = holistic.process(image) #Prever poses
if (not results.pose_landmarks):
#Não reconheceu bem, voltar as cores para RGB para ver se reconhece melhor
image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
results = holistic.process(image)
if results.pose_landmarks:
print("Word: " + word + ", frame: " + str(frame) + ", time: " + str(time))
#Cria uma linha do frame com dados do frame/vídeo
line = [
wordId,
word,
fps,
frame_count,
duration,
image_width,
image_height,
frame,
time
]
line = createLine(results, line)
data.append(line)
createImage(results, image, output, video, frame)
frame = frame + 1
else:
#Não reconheceu nada da pose.
print("IGNORADO Word: " + word + ", frame: " + str(frame) + ", time: " + str(time))
createImage(results, image, output, video + "FALHA.mp4", frame)
#frame = frame + 1
ignored += 1
exit()
return data
def createLineEmptyValue(line: list, size = 40, value = 0) -> list:
"""Cria valores vazios por falta de reconhecimento de pose/mão"""
for x in range(size):
line.append(value)
return line
def createLine(results, line) -> list:
"""Obtem todas as posições de pose e mão e adiciona na linha do dataset"""
line = createLinePose(results, line)
handSize = 40
if (WITH_Z):
handSize = 60
if (results.left_hand_landmarks != None):
line = createLineHand(results.left_hand_landmarks.landmark, line)
else:
line = createLineEmptyValue(line, handSize, 0)
if (results.right_hand_landmarks != None):
line = createLineHand(results.right_hand_landmarks.landmark, line)
else:
line = createLineEmptyValue(line, handSize, 0)
return line
def createLinePose(results, line: list) -> list:
"""Obtem os valores de poses do corpo"""
line.append(results.pose_landmarks.landmark[mp_holistic.PoseLandmark.NOSE].x)
line.append(results.pose_landmarks.landmark[mp_holistic.PoseLandmark.NOSE].y)
if WITH_Z: line.append(results.pose_landmarks.landmark[mp_holistic.PoseLandmark.NOSE].z)
line.append(results.pose_landmarks.landmark[mp_holistic.PoseLandmark.LEFT_EYE].x)
line.append(results.pose_landmarks.landmark[mp_holistic.PoseLandmark.LEFT_EYE].y)
if WITH_Z: line.append(results.pose_landmarks.landmark[mp_holistic.PoseLandmark.LEFT_EYE].z)
line.append(results.pose_landmarks.landmark[mp_holistic.PoseLandmark.LEFT_EAR].x)
line.append(results.pose_landmarks.landmark[mp_holistic.PoseLandmark.LEFT_EAR].y)
if WITH_Z: line.append(results.pose_landmarks.landmark[mp_holistic.PoseLandmark.LEFT_EAR].z)
line.append(results.pose_landmarks.landmark[mp_holistic.PoseLandmark.RIGHT_EYE].x)
line.append(results.pose_landmarks.landmark[mp_holistic.PoseLandmark.RIGHT_EYE].y)
if WITH_Z: line.append(results.pose_landmarks.landmark[mp_holistic.PoseLandmark.RIGHT_EYE].z)
line.append(results.pose_landmarks.landmark[mp_holistic.PoseLandmark.RIGHT_EAR].x)
line.append(results.pose_landmarks.landmark[mp_holistic.PoseLandmark.RIGHT_EAR].y)
if WITH_Z: line.append(results.pose_landmarks.landmark[mp_holistic.PoseLandmark.RIGHT_EAR].z)
line.append(results.pose_landmarks.landmark[mp_holistic.PoseLandmark.MOUTH_LEFT].x)
line.append(results.pose_landmarks.landmark[mp_holistic.PoseLandmark.MOUTH_LEFT].y)
if WITH_Z: line.append(results.pose_landmarks.landmark[mp_holistic.PoseLandmark.MOUTH_LEFT].z)
line.append(results.pose_landmarks.landmark[mp_holistic.PoseLandmark.MOUTH_RIGHT].x)
line.append(results.pose_landmarks.landmark[mp_holistic.PoseLandmark.MOUTH_RIGHT].y)
if WITH_Z: line.append(results.pose_landmarks.landmark[mp_holistic.PoseLandmark.MOUTH_RIGHT].z)
line.append(results.pose_landmarks.landmark[mp_holistic.PoseLandmark.LEFT_SHOULDER].x)
line.append(results.pose_landmarks.landmark[mp_holistic.PoseLandmark.LEFT_SHOULDER].y)
if WITH_Z: line.append(results.pose_landmarks.landmark[mp_holistic.PoseLandmark.LEFT_SHOULDER].z)
line.append(results.pose_landmarks.landmark[mp_holistic.PoseLandmark.RIGHT_SHOULDER].x)
line.append(results.pose_landmarks.landmark[mp_holistic.PoseLandmark.RIGHT_SHOULDER].y)
if WITH_Z: line.append(results.pose_landmarks.landmark[mp_holistic.PoseLandmark.RIGHT_SHOULDER].z)
line.append(results.pose_landmarks.landmark[mp_holistic.PoseLandmark.LEFT_ELBOW].x)
line.append(results.pose_landmarks.landmark[mp_holistic.PoseLandmark.LEFT_ELBOW].y)
if WITH_Z: line.append(results.pose_landmarks.landmark[mp_holistic.PoseLandmark.LEFT_ELBOW].z)
line.append(results.pose_landmarks.landmark[mp_holistic.PoseLandmark.RIGHT_ELBOW].x)
line.append(results.pose_landmarks.landmark[mp_holistic.PoseLandmark.RIGHT_ELBOW].y)
if WITH_Z: line.append(results.pose_landmarks.landmark[mp_holistic.PoseLandmark.RIGHT_ELBOW].z)
line.append(results.pose_landmarks.landmark[mp_holistic.PoseLandmark.LEFT_WRIST].x)
line.append(results.pose_landmarks.landmark[mp_holistic.PoseLandmark.LEFT_WRIST].y)
if WITH_Z: line.append(results.pose_landmarks.landmark[mp_holistic.PoseLandmark.LEFT_WRIST].z)
line.append(results.pose_landmarks.landmark[mp_holistic.PoseLandmark.RIGHT_WRIST].x)
line.append(results.pose_landmarks.landmark[mp_holistic.PoseLandmark.RIGHT_WRIST].y)
if WITH_Z: line.append(results.pose_landmarks.landmark[mp_holistic.PoseLandmark.RIGHT_WRIST].z)
line.append(results.pose_landmarks.landmark[mp_holistic.PoseLandmark.LEFT_HIP].x)
line.append(results.pose_landmarks.landmark[mp_holistic.PoseLandmark.LEFT_HIP].y)
if WITH_Z: line.append(results.pose_landmarks.landmark[mp_holistic.PoseLandmark.LEFT_HIP].z)
line.append(results.pose_landmarks.landmark[mp_holistic.PoseLandmark.RIGHT_HIP].x)
line.append(results.pose_landmarks.landmark[mp_holistic.PoseLandmark.RIGHT_HIP].y)
if WITH_Z: line.append(results.pose_landmarks.landmark[mp_holistic.PoseLandmark.RIGHT_HIP].z)
return line
def createLineHand(landmark, line: list) -> list:
"""Obtem valores de poses da mão"""
#line.append(landmark[mp_holistic.HandLandmark.WRIST].x)
#line.append(landmark[mp_holistic.HandLandmark.WRIST].y)
line.append(landmark[mp_holistic.HandLandmark.THUMB_CMC].x)
line.append(landmark[mp_holistic.HandLandmark.THUMB_CMC].y)
if WITH_Z: line.append(landmark[mp_holistic.HandLandmark.THUMB_CMC].z)
line.append(landmark[mp_holistic.HandLandmark.THUMB_MCP].x)
line.append(landmark[mp_holistic.HandLandmark.THUMB_MCP].y)
if WITH_Z: line.append(landmark[mp_holistic.HandLandmark.THUMB_MCP].z)
line.append(landmark[mp_holistic.HandLandmark.THUMB_IP].x)
line.append(landmark[mp_holistic.HandLandmark.THUMB_IP].y)
if WITH_Z: line.append(landmark[mp_holistic.HandLandmark.THUMB_IP].z)
line.append(landmark[mp_holistic.HandLandmark.THUMB_TIP].x)
line.append(landmark[mp_holistic.HandLandmark.THUMB_TIP].y)
if WITH_Z: line.append(landmark[mp_holistic.HandLandmark.THUMB_TIP].z)
line.append(landmark[mp_holistic.HandLandmark.INDEX_FINGER_MCP].x)
line.append(landmark[mp_holistic.HandLandmark.INDEX_FINGER_MCP].y)
if WITH_Z: line.append(landmark[mp_holistic.HandLandmark.INDEX_FINGER_MCP].z)
line.append(landmark[mp_holistic.HandLandmark.INDEX_FINGER_PIP].x)
line.append(landmark[mp_holistic.HandLandmark.INDEX_FINGER_PIP].y)
if WITH_Z: line.append(landmark[mp_holistic.HandLandmark.INDEX_FINGER_PIP].z)
line.append(landmark[mp_holistic.HandLandmark.INDEX_FINGER_DIP].x)
line.append(landmark[mp_holistic.HandLandmark.INDEX_FINGER_DIP].y)
if WITH_Z: line.append(landmark[mp_holistic.HandLandmark.INDEX_FINGER_DIP].z)
line.append(landmark[mp_holistic.HandLandmark.INDEX_FINGER_TIP].x)
line.append(landmark[mp_holistic.HandLandmark.INDEX_FINGER_TIP].y)
if WITH_Z: line.append(landmark[mp_holistic.HandLandmark.INDEX_FINGER_TIP].z)
line.append(landmark[mp_holistic.HandLandmark.MIDDLE_FINGER_MCP].x)
line.append(landmark[mp_holistic.HandLandmark.MIDDLE_FINGER_MCP].y)
if WITH_Z: line.append(landmark[mp_holistic.HandLandmark.MIDDLE_FINGER_MCP].z)
line.append(landmark[mp_holistic.HandLandmark.MIDDLE_FINGER_PIP].x)
line.append(landmark[mp_holistic.HandLandmark.MIDDLE_FINGER_PIP].y)
if WITH_Z: line.append(landmark[mp_holistic.HandLandmark.MIDDLE_FINGER_PIP].z)
line.append(landmark[mp_holistic.HandLandmark.MIDDLE_FINGER_DIP].x)
line.append(landmark[mp_holistic.HandLandmark.MIDDLE_FINGER_DIP].y)
if WITH_Z: line.append(landmark[mp_holistic.HandLandmark.MIDDLE_FINGER_DIP].z)
line.append(landmark[mp_holistic.HandLandmark.MIDDLE_FINGER_TIP].x)
line.append(landmark[mp_holistic.HandLandmark.MIDDLE_FINGER_TIP].y)
if WITH_Z: line.append(landmark[mp_holistic.HandLandmark.MIDDLE_FINGER_TIP].z)
line.append(landmark[mp_holistic.HandLandmark.RING_FINGER_MCP].x)
line.append(landmark[mp_holistic.HandLandmark.RING_FINGER_MCP].y)
if WITH_Z: line.append(landmark[mp_holistic.HandLandmark.RING_FINGER_MCP].z)
line.append(landmark[mp_holistic.HandLandmark.RING_FINGER_PIP].x)
line.append(landmark[mp_holistic.HandLandmark.RING_FINGER_PIP].y)
if WITH_Z: line.append(landmark[mp_holistic.HandLandmark.RING_FINGER_PIP].z)
line.append(landmark[mp_holistic.HandLandmark.RING_FINGER_DIP].x)
line.append(landmark[mp_holistic.HandLandmark.RING_FINGER_DIP].y)
if WITH_Z: line.append(landmark[mp_holistic.HandLandmark.RING_FINGER_DIP].z)
line.append(landmark[mp_holistic.HandLandmark.RING_FINGER_TIP].x)
line.append(landmark[mp_holistic.HandLandmark.RING_FINGER_TIP].y)
if WITH_Z: line.append(landmark[mp_holistic.HandLandmark.RING_FINGER_TIP].z)
line.append(landmark[mp_holistic.HandLandmark.PINKY_MCP].x)
line.append(landmark[mp_holistic.HandLandmark.PINKY_MCP].y)
if WITH_Z: line.append(landmark[mp_holistic.HandLandmark.PINKY_MCP].z)
line.append(landmark[mp_holistic.HandLandmark.PINKY_PIP].x)
line.append(landmark[mp_holistic.HandLandmark.PINKY_PIP].y)
if WITH_Z: line.append(landmark[mp_holistic.HandLandmark.PINKY_PIP].z)
line.append(landmark[mp_holistic.HandLandmark.PINKY_DIP].x)
line.append(landmark[mp_holistic.HandLandmark.PINKY_DIP].y)
if WITH_Z: line.append(landmark[mp_holistic.HandLandmark.PINKY_DIP].z)
line.append(landmark[mp_holistic.HandLandmark.PINKY_TIP].x)
line.append(landmark[mp_holistic.HandLandmark.PINKY_TIP].y)
if WITH_Z: line.append(landmark[mp_holistic.HandLandmark.PINKY_TIP].z)
return line
def createImage(results, image, wordPath, video, frame):
"""Cria a imagem para verificação do processo"""
h, w = image.shape[:2]
annotated_image = np.zeros((DESIRED_WIDTH, DESIRED_HEIGHT, 3), np.uint8)
annotated_image[:] = (255, 255, 255)
mp_drawing.draw_landmarks(annotated_image, results.left_hand_landmarks, mp_holistic.HAND_CONNECTIONS)
mp_drawing.draw_landmarks(annotated_image, results.right_hand_landmarks, mp_holistic.HAND_CONNECTIONS)
mp_drawing.draw_landmarks(image=annotated_image, landmark_list=results.pose_landmarks, connections=mp_holistic.POSE_CONNECTIONS)
videoPath = Path(video).stem
imageFile = os.path.join(wordPath, videoPath)
imageFile = unicodedata.normalize('NFD', imageFile)\
.encode('ascii', 'ignore')\
.decode("utf-8")
if (not os.path.isdir(imageFile)):
os.makedirs(imageFile)
imageFile = os.path.join(imageFile, "frame_" + str(frame) + ".png" )
imageFile = unicodedata.normalize('NFD', imageFile)\
.encode('ascii', 'ignore')\
.decode("utf-8")
cv2.imwrite(imageFile, annotated_image)
def generateColumns(columns: list, withZ: bool) -> list:
allColumns = list()
for column in columns:
allColumns.append(column + "_X")
allColumns.append(column + "_Y")
if withZ: allColumns.append(column + "_Z")
return allColumns
def getColumns():
"""Obtem os nomes das colunas para salvar no CSV"""
columns = [
"ID",
"WORD",
"FPS",
"FRAME_COUNT",
"DURATION",
"WIDTH",
"HEIGHT",
"FRAME",
"TIME"]
toGenerate = [
"NOSE",
"LEFT_EYE",
"LEFT_EAR",
"RIGHT_EYE",
"RIGHT_EAR",
"MOUTH_LEFT",
"MOUTH_RIGHT",
"LEFT_SHOULDER",
"RIGHT_SHOULDER",
"LEFT_ELBOW",
"RIGHT_ELBOW",
"LEFT_WRIST",
"RIGHT_WRIST",
"LEFT_HIP",
"RIGHT_HIP",
"LEFT_HAND_THUMB_CMC",
"LEFT_HAND_THUMB_MCP",
"LEFT_HAND_THUMB_IP",
"LEFT_HAND_THUMB_TIP",
"LEFT_HAND_INDEX_FINGER_MCP",
"LEFT_HAND_INDEX_FINGER_PIP",
"LEFT_HAND_INDEX_FINGER_DIP",
"LEFT_HAND_INDEX_FINGER_TIP",
"LEFT_HAND_MIDDLE_FINGER_MCP",
"LEFT_HAND_MIDDLE_FINGER_PIP",
"LEFT_HAND_MIDDLE_FINGER_DIP",
"LEFT_HAND_MIDDLE_FINGER_TIP",
"LEFT_HAND_RING_FINGER_MCP",
"LEFT_HAND_RING_FINGER_PIP",
"LEFT_HAND_RING_FINGER_DIP",
"LEFT_HAND_RING_FINGER_TIP",
"LEFT_HAND_PINKY_MCP",
"LEFT_HAND_PINKY_PIP",
"LEFT_HAND_PINKY_DIP",
"LEFT_HAND_PINKY_TIP",
"RIGHT_HAND_THUMB_CMC",
"RIGHT_HAND_THUMB_MCP",
"RIGHT_HAND_THUMB_IP",
"RIGHT_HAND_THUMB_TIP",
"RIGHT_HAND_INDEX_FINGER_MCP",
"RIGHT_HAND_INDEX_FINGER_PIP",
"RIGHT_HAND_INDEX_FINGER_DIP",
"RIGHT_HAND_INDEX_FINGER_TIP",
"RIGHT_HAND_MIDDLE_FINGER_MCP",
"RIGHT_HAND_MIDDLE_FINGER_PIP",
"RIGHT_HAND_MIDDLE_FINGER_DIP",
"RIGHT_HAND_MIDDLE_FINGER_TIP",
"RIGHT_HAND_RING_FINGER_MCP",
"RIGHT_HAND_RING_FINGER_PIP",
"RIGHT_HAND_RING_FINGER_DIP",
"RIGHT_HAND_RING_FINGER_TIP",
"RIGHT_HAND_PINKY_MCP",
"RIGHT_HAND_PINKY_PIP",
"RIGHT_HAND_PINKY_DIP",
"RIGHT_HAND_PINKY_TIP",
]
columns = columns + generateColumns(toGenerate, WITH_Z)
return columns
def saveData(data):
"""Salva o dataset gerado"""
columns = getColumns()
df = pd.DataFrame(data, columns=columns)
df.to_csv(r"./output/words_dataset.csv", index = False)
print(df)
print("Frames ignorados: " + str(ignored))
#Inicia o processo, pelo método process:
process()