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2021-208
Commit 64a584d0 authored by dewmalFernando's avatar dewmalFernando
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V1.17

parent 5a2bf325
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Showing with 503 additions and 241 deletions
UI/app.js
View file @ 64a584d0
...@@ -33,12 +33,14 @@ if(result != null){ ...@@ -33,12 +33,14 @@ if(result != null){
<!-- <p>Your account details are below:</p> --> <!-- <p>Your account details are below:</p> -->
<table > <table >
<tr > <tr >
<td>Enhancement type :</td> <td>Contrast Adjustment : Clahe</td>
</tr> </tr>
<tr> <tr>
<td>Method Type :</td> <td>Improve Image Shapness : Unsharp masking</td>
</tr>
<tr>
<td>Noise Type : Gaussian noise</td>
</tr> </tr>
</table> </table>
</div> </div>
</div> </div>
...@@ -247,7 +249,7 @@ function insertVideoAbnormal(newVideo) { ...@@ -247,7 +249,7 @@ function insertVideoAbnormal(newVideo) {
console.log(data) console.log(data)
console.log(data.id) console.log(data.id)
data.path = "E:\\BACKBONE\\videos\\Input.mp4" //data.path = "E:\\BACKBONE\\videos\\Input.mp4"
let id = data.id let id = data.id
fetch(`http://127.0.0.1:5000/startAbnormalBehaviourDetection`, { fetch(`http://127.0.0.1:5000/startAbnormalBehaviourDetection`, {
......
abnormal_behavior_detection/HumanDetection/Human_Detection_Video.py
View file @ 64a584d0
...@@ -10,6 +10,7 @@ from tifffile import askopenfilename ...@@ -10,6 +10,7 @@ from tifffile import askopenfilename
def capture_humans(path): def capture_humans(path):
# path = "E:\\BACKBONE\\videos\\Input.mp4"
print(path) print(path)
protopath = "E:/BACKBONE/abnormal_behavior_detection/Models/Human Detection/MobileNetSSD_deploy.prototxt" protopath = "E:/BACKBONE/abnormal_behavior_detection/Models/Human Detection/MobileNetSSD_deploy.prototxt"
......
app.py
View file @ 64a584d0
...@@ -38,111 +38,6 @@ video_files = VideoSchema(many=True) ...@@ -38,111 +38,6 @@ video_files = VideoSchema(many=True)
value_field = Values() value_field = Values()
class EnhancedVideos(db.Model):
id = db.Column(db.Integer, primary_key=True)
name = db.Column(db.String(50))
path = db.Column(db.String(150))
def __init__(self, name, path):
self.name = name
self.path = path
class EnhancedVideosSchema(ma.Schema):
class Meta:
fields = ('id', 'name', 'path')
class EnhancedValues:
class Meta:
fields = 'value'
EnhancedVideoFile = EnhancedVideosSchema()
EnhancedVideo_value_field = EnhancedValues()
class AbnormalBehaviourDetails(db.Model):
id = db.Column(db.Integer, primary_key=True)
typeOfAttack = db.Column(db.String(100))
usedWeapon = db.Column(db.String(100))
def __init__(self, typeOfAttack, usedWeapon):
self.usedWeapon = usedWeapon
self.typeOfAttack = typeOfAttack
class AbnormalBehaviourSchema(ma.Schema):
class Meta:
fields = ('id', 'usedWeapon', 'typeOfAttack')
class Values:
class Meta:
fields = 'value'
AbnormalBehaviour = AbnormalBehaviourSchema()
AbnormalBehaviours = AbnormalBehaviourSchema(many=True)
AbnormalBehaviour_value_field = Values()
# For Face Recognition
class FaceRecognitionDetails(db.Model):
id = db.Column(db.Integer, primary_key=True)
name = db.Column(db.String(100))
path = db.Column(db.String(250))
def __init__(self, name, path):
self.name = name
self.path = path
class FaceRecognitionSchema(ma.Schema):
class Meta:
fields = ('id', 'name', 'path')
class Values:
class Meta:
fields = 'value'
faceRecognitionSchema = FaceRecognitionSchema()
faceRecognitionSchemas = FaceRecognitionSchema(many=True)
FaceRecognitionSchema_field = Values()
# Figure
class FigureDetails(db.Model): # Articles
id = db.Column(db.Integer, primary_key=True)
age = db.Column(db.String(20))
gender = db.Column(db.String(6))
height = db.Column(db.Float())
def __init__(self, age, gender, height):
self.age = age
self.gender = gender
self.height = height
class FigureSchema(ma.Schema):
class Meta:
fields = ('id', 'age', 'gender', 'height')
class Values():
class Meta:
fields = 'value'
figure_data = FigureSchema()
figure_datas = FigureSchema(many=True)
@app.route('/get', methods=['GET']) @app.route('/get', methods=['GET'])
def get_videos(): def get_videos():
videos = VideoDetails.query.all() videos = VideoDetails.query.all()
...@@ -178,6 +73,34 @@ def add_video(): ...@@ -178,6 +73,34 @@ def add_video():
return video_file.jsonify(video) return video_file.jsonify(video)
""" Start of the image enhancement function """
class EnhancedVideos(db.Model):
id = db.Column(db.Integer, primary_key=True)
name = db.Column(db.String(50))
path = db.Column(db.String(150))
def __init__(self, name, path):
self.name = name
self.path = path
class EnhancedVideosSchema(ma.Schema):
class Meta:
fields = ('id', 'name', 'path')
class EnhancedValues:
class Meta:
fields = 'value'
EnhancedVideoFile = EnhancedVideosSchema()
EnhancedVideo_value_field = EnhancedValues()
@app.route('/StartImageEnhance', methods=['POST']) @app.route('/StartImageEnhance', methods=['POST'])
def StartImageEnhance(): def StartImageEnhance():
from imageEnhancement import VidToFrames from imageEnhancement import VidToFrames
...@@ -199,6 +122,37 @@ def StartImageEnhance(): ...@@ -199,6 +122,37 @@ def StartImageEnhance():
return values return values
""" End of the image enhancement function """
""" Start of the abnormal behavior detection function """
class AbnormalBehaviourDetails(db.Model):
id = db.Column(db.Integer, primary_key=True)
typeOfAttack = db.Column(db.String(100))
usedWeapon = db.Column(db.String(100))
def __init__(self, typeOfAttack, usedWeapon):
self.usedWeapon = usedWeapon
self.typeOfAttack = typeOfAttack
class AbnormalBehaviourSchema(ma.Schema):
class Meta:
fields = ('id', 'usedWeapon', 'typeOfAttack')
class Values:
class Meta:
fields = 'value'
AbnormalBehaviour = AbnormalBehaviourSchema()
AbnormalBehaviours = AbnormalBehaviourSchema(many=True)
AbnormalBehaviour_value_field = Values()
@app.route('/startAbnormalBehaviourDetection', methods=['POST']) @app.route('/startAbnormalBehaviourDetection', methods=['POST'])
def startAbnormalBehaviourDetection(): def startAbnormalBehaviourDetection():
from abnormal_behavior_detection.ScriptsOrder import Scripts_Order from abnormal_behavior_detection.ScriptsOrder import Scripts_Order
...@@ -214,85 +168,78 @@ def startAbnormalBehaviourDetection(): ...@@ -214,85 +168,78 @@ def startAbnormalBehaviourDetection():
# data = {'id': id, 'name': name, 'path': path} # data = {'id': id, 'name': name, 'path': path}
# Human_Detection_Video.capture_humans('C:/Users/Givindu/Desktop/New folder/'+path[2]) # Human_Detection_Video.capture_humans('C:/Users/Givindu/Desktop/New folder/'+path[2])
AbDetection = Scripts_Order.data(path) print("app -> " + path)
AbDetection = Scripts_Order.data(
"E:\\BACKBONE\\image_enhancement\\EnhancedVideos\\EnhancedVideo1\\" + path.split("\\")[2])
return jsonify(AbDetection) return jsonify(AbDetection)
@app.route('/RunFaceRecognition/<id>/', methods=['POST']) class behavior_details(db.Model):
def RunFaceRecognition(id): id = db.Column(db.Integer, primary_key=True)
from face_detection_recognition import script_file incident_type = db.Column(db.String(100))
id = request.json['id'] used_weapon = db.Column(db.String(100))
name = request.json['name'] detected_time = db.Column(db.Float())
path = request.json['path']
# data = get_video(id)
path = str(path).split('\\') def __init__(self, incident_type, used_weapon, detected_time):
print(path) self.incident_type = incident_type
self.used_weapon = used_weapon
self.detected_time = detected_time
data = {'id': id, 'name': name, 'path': path}
# data = {'id': id, 'name': name, 'path': path}
# FaceRecognition = Scripts.data('C:/Users/Praveen/Desktop/Research project/PP1 input/Input video/' + path[2]) class behavior_details_schema(ma.Schema):
FDRecognition = script_file.data('E:\\BACKBONE\\videos\\' + path[2]) class Meta:
fields = (
'id', 'incident_type', 'used_weapon', 'detected_time')
return jsonify(FDRecognition)
behaviors_schema = behavior_details_schema()
behaviors_schema = behavior_details_schema(many=True)
@app.route('/StartFaceRecognition', methods=['POST'])
def StartFaceRecognition():
from face_detection_recognition import script_file
# path = request.json['path'] class criminal_result_schema(ma.Schema):
# # data = get_video(id) class Meta:
# fields = (
# path = str(path).split('\\') 'id', 'incident_type', 'used_weapon', 'detected_time')
# print(path)
# FaceRecognition = Scripts.data('C:/Users/Praveen/Desktop/Research project/PP1 input/Input video/' + path[2])
FDRecognition = script_file.imagetovideo_process(
'E:/BACKBONE/abnormal_behavior_detection/frames/Suspects with Weapons/')
return jsonify(FDRecognition) criminal_schema = criminal_result_schema()
criminals_schema = criminal_result_schema(many=True)
""" End of the abnormal behavior detection function """
@app.route('/RunFigureRecognition', methods=['POST']) """ Start of the face recognition function """
def RunFigureRecognition():
from figure_recognition.ScriptList import Script_List
path = request.json['path']
# data = get_video(id)
path = str(path).split('\\')
print(path)
# data = {'id': id, 'name': name, 'path': path}
# data = {'id': id, 'name': name, 'path': path}
age, gender = Script_List.data('C:/Users/USER/Desktop/Research/image/' + path[2])
# figure_data.jsonify({'id':0, 'age':age, 'gender':gender, 'height':0}) # For Face Recognition
return jsonify(age, gender) class FaceRecognitionDetails(db.Model):
id = db.Column(db.Integer, primary_key=True)
name = db.Column(db.String(100))
path = db.Column(db.String(250))
def __init__(self, name, path):
self.name = name
self.path = path
@app.route('/StartFigureRecognition', methods=['GET']) class FaceRecognitionSchema(ma.Schema):
def StartFigureRecognition(): class Meta:
from figure_recognition.ScriptList import Script_List fields = ('id', 'name', 'path')
age, gender = Script_List.figure()
# figure_data.jsonify({'id':0, 'age':age, 'gender':gender, 'height':0}) class Values:
return jsonify(age, gender) class Meta:
fields = 'value'
@app.route('/SaveFigureData', methods=['POST']) faceRecognitionSchema = FaceRecognitionSchema()
def SaveFigureData(): faceRecognitionSchemas = FaceRecognitionSchema(many=True)
age = request.json['age']
gender = request.json['gender']
height = 5.4
data = FigureDetails(age, gender, height) FaceRecognitionSchema_field = Values()
db.session.add(data)
db.session.commit()
return jsonify("Done"); """ End of the abnormal behavior detection function """
""" Start of the face detection function """
# Criminals table input fields # Criminals table input fields
...@@ -405,28 +352,6 @@ def update_Criminals_details(id): ...@@ -405,28 +352,6 @@ def update_Criminals_details(id):
return criminals_Schema.jsonify(criminals_details) return criminals_Schema.jsonify(criminals_details)
class behavior_details(db.Model):
id = db.Column(db.Integer, primary_key=True)
incident_type = db.Column(db.String(100))
used_weapon = db.Column(db.String(100))
detected_time = db.Column(db.Float())
def __init__(self, incident_type, used_weapon, detected_time):
self.incident_type = incident_type
self.used_weapon = used_weapon
self.detected_time = detected_time
class behavior_details_schema(ma.Schema):
class Meta:
fields = (
'id', 'incident_type', 'used_weapon', 'detected_time')
behaviors_schema = behavior_details_schema()
behaviors_schema = behavior_details_schema(many=True)
class criminal_result(db.Model): class criminal_result(db.Model):
id = db.Column(db.Integer, primary_key=True) id = db.Column(db.Integer, primary_key=True)
Name = db.Column(db.String(100)) Name = db.Column(db.String(100))
...@@ -451,14 +376,73 @@ class criminal_result(db.Model): ...@@ -451,14 +376,73 @@ class criminal_result(db.Model):
self.Crimes = Crimes self.Crimes = Crimes
class criminal_result_schema(ma.Schema): @app.route('/RunFaceRecognition/<id>/', methods=['POST'])
def RunFaceRecognition(id):
from face_detection_recognition import script_file
id = request.json['id']
name = request.json['name']
path = request.json['path']
# data = get_video(id)
path = str(path).split('\\')
print(path)
data = {'id': id, 'name': name, 'path': path}
# data = {'id': id, 'name': name, 'path': path}
# FaceRecognition = Scripts.data('C:/Users/Praveen/Desktop/Research project/PP1 input/Input video/' + path[2])
FDRecognition = script_file.data('E:\\BACKBONE\\videos\\' + path[2])
return jsonify(FDRecognition)
@app.route('/StartFaceRecognition', methods=['POST'])
def StartFaceRecognition():
from face_detection_recognition import script_file
# path = request.json['path']
# # data = get_video(id)
#
# path = str(path).split('\\')
# print(path)
# FaceRecognition = Scripts.data('C:/Users/Praveen/Desktop/Research project/PP1 input/Input video/' + path[2])
FDRecognition = script_file.imagetovideo_process(
'E:/BACKBONE/abnormal_behavior_detection/frames/Suspects with Weapons/')
return jsonify(FDRecognition)
""" End of the face detection function """
""" Start of the figure recognition function """
# Figure
class FigureDetails(db.Model): # Articles
id = db.Column(db.Integer, primary_key=True)
age = db.Column(db.String(20))
gender = db.Column(db.String(6))
height = db.Column(db.Float())
def __init__(self, age, gender, height):
self.age = age
self.gender = gender
self.height = height
class FigureSchema(ma.Schema):
class Meta: class Meta:
fields = ( fields = ('id', 'age', 'gender', 'height')
'id', 'incident_type', 'used_weapon', 'detected_time')
criminal_schema = criminal_result_schema() class Values():
criminals_schema = criminal_result_schema(many=True) class Meta:
fields = 'value'
figure_data = FigureSchema()
figure_datas = FigureSchema(many=True)
@app.route('/GetAllData', methods=['GET']) @app.route('/GetAllData', methods=['GET'])
...@@ -498,5 +482,46 @@ def GetAllData(): ...@@ -498,5 +482,46 @@ def GetAllData():
return jsonify(data1, data2, data3) return jsonify(data1, data2, data3)
@app.route('/RunFigureRecognition', methods=['POST'])
def RunFigureRecognition():
from figure_recognition.ScriptList import Script_List
path = request.json['path']
# data = get_video(id)
path = str(path).split('\\')
print(path)
# data = {'id': id, 'name': name, 'path': path}
# data = {'id': id, 'name': name, 'path': path}
age, gender = Script_List.data('C:/Users/USER/Desktop/Research/image/' + path[2])
# figure_data.jsonify({'id':0, 'age':age, 'gender':gender, 'height':0})
return jsonify(age, gender)
@app.route('/StartFigureRecognition', methods=['GET'])
def StartFigureRecognition():
from figure_recognition.ScriptList import Script_List
age, gender = Script_List.figure()
# figure_data.jsonify({'id':0, 'age':age, 'gender':gender, 'height':0})
return jsonify(age, gender)
@app.route('/SaveFigureData', methods=['POST'])
def SaveFigureData():
age = request.json['age']
gender = request.json['gender']
height = 5.4
data = FigureDetails(age, gender, height)
db.session.add(data)
db.session.commit()
return jsonify("Done");
""" End of the figure recognition function """
if __name__ == "__main__": if __name__ == "__main__":
app.run(debug=True) app.run(debug=True)
imageEnhancement/ContrastEdjustments.py 0 → 100644
View file @ 64a584d0
import cv2
import os
from imageEnhancement import ImageSharpening
from imageEnhancement import CreateNewFolderForFrames
def adjustContrast(folder, rate):
contrastAdjustedFrames = CreateNewFolderForFrames.createFolderForContrasted(folder)
path = "E:\\BACKBONE\\image_enhancement\\Frames\\" + folder
count = 10000000
for file in os.listdir(path):
if file.endswith(".jpg"):
# -----Reading the image-----------------------------------------------------
img = cv2.imread(path + "\\" + file)
# -----Converting image to LAB Color model-----------------------------------
lab = cv2.cvtColor(img, cv2.COLOR_BGR2LAB)
# -----Splitting the LAB image to different channels-------------------------
l, a, b = cv2.split(lab)
# -----Applying CLAHE to L-channel-------------------------------------------
clahe = cv2.createCLAHE(clipLimit=3.0, tileGridSize=(5, 5))
cl = clahe.apply(l)
# -----Merge the CLAHE enhanced L-channel with the a and b channel-----------
limg = cv2.merge((cl, a, b))
# -----Converting image from LAB Color model to RGB model--------------------
final = cv2.cvtColor(limg, cv2.COLOR_LAB2BGR)
cv2.imwrite(contrastAdjustedFrames + "\\%d.jpg" % count, final)
count += 1
value = ImageSharpening.imageSharp(folder, contrastAdjustedFrames, rate)
return value
imageEnhancement/CreateNewFolderForFrames.py
View file @ 64a584d0
# Python program to explain os.mkdir() method
# importing os module
import os import os
def createFolder(): def createFolder():
parentPath = "E:\\BACKBONE\\image_enhancement\\Frames" parentPath = "E:\\BACKBONE\\image_enhancement\\Frames"
...@@ -36,9 +34,10 @@ def createFolder(): ...@@ -36,9 +34,10 @@ def createFolder():
print("Directory '% s' created" % directory) print("Directory '% s' created" % directory)
return directory return directory
def createFolderForEnhancedFrames(folderName): def createFolderForEnhancedFrames(folderName):
print("folder name in createFolderForEnhancedFrames : " +folderName) print("folder name in createFolderForEnhancedFrames : " + folderName)
parentPath = "E:\\BACKBONE\\image_enhancement\\Frames\\"+folderName parentPath = "E:\\BACKBONE\\image_enhancement\\Frames\\" + folderName
totalFiles = 0 totalFiles = 0
totalDir = 0 totalDir = 0
...@@ -58,7 +57,7 @@ def createFolderForEnhancedFrames(folderName): ...@@ -58,7 +57,7 @@ def createFolderForEnhancedFrames(folderName):
directory = "Enhanced_Frames" + str(count) directory = "Enhanced_Frames" + str(count)
# Parent Directory path # Parent Directory path
parent_dir = "E:\\BACKBONE\\image_enhancement\\Frames\\"+folderName parent_dir = "E:\\BACKBONE\\image_enhancement\\Frames\\" + folderName
# Path # Path
path = os.path.join(parent_dir, directory) path = os.path.join(parent_dir, directory)
...@@ -71,7 +70,142 @@ def createFolderForEnhancedFrames(folderName): ...@@ -71,7 +70,142 @@ def createFolderForEnhancedFrames(folderName):
print("Directory '% s' created" % directory) print("Directory '% s' created" % directory)
return directory return directory
# if __name__ == '__main__':
# # Calling the function
# createFolder()
def createFolderForContrasted(folderName):
parentPath = "E:\\BACKBONE\\image_enhancement\\Frames\\" + folderName
totalFiles = 0
totalDir = 0
for base, dirs, files in os.walk(parentPath):
print('Searching in : ', base)
for directories in dirs:
totalDir += 1
for Files in files:
totalFiles += 1
print('Total Number of directories', totalDir)
count = totalDir + 1
# Directory
directory = "Contrast_Adjusted_Frames" + str(count)
# Parent Directory path
parent_dir = "E:\\BACKBONE\\image_enhancement\\Frames\\" + folderName
# Path
path = os.path.join(parent_dir, directory)
# Create the directory
# 'GeeksForGeeks' in
# '/home / User / Documents'
os.mkdir(path)
print("path : " + path)
print("Directory '% s' created" % directory)
return path
def createFolderForSharpImages(folderName):
parentPath = "E:\\BACKBONE\\image_enhancement\\Frames\\" + folderName
totalFiles = 0
totalDir = 0
for base, dirs, files in os.walk(parentPath):
print('Searching in : ', base)
for directories in dirs:
totalDir += 1
for Files in files:
totalFiles += 1
print('Total Number of directories', totalDir)
count = totalDir + 1
# Directory
directory = "Sharp_Frames" + str(count)
# Parent Directory path
parent_dir = "E:\\BACKBONE\\image_enhancement\\Frames\\" + folderName
# Path
path = os.path.join(parent_dir, directory)
# Create the directory
# 'GeeksForGeeks' in
# '/home / User / Documents'
os.mkdir(path)
print("path : " + path)
print("Directory '% s' created" % directory)
return path
def DenoiseGaussian(folderName):
parentPath = "E:\\BACKBONE\\image_enhancement\\Frames\\" + folderName
totalFiles = 0
totalDir = 0
for base, dirs, files in os.walk(parentPath):
print('Searching in : ', base)
for directories in dirs:
totalDir += 1
for Files in files:
totalFiles += 1
print('Total Number of directories', totalDir)
count = totalDir + 1
# Directory
directory = "Gaussian_Denoised_Frames" + str(count)
# Parent Directory path
parent_dir = "E:\\BACKBONE\\image_enhancement\\Frames\\" + folderName
# Path
path = os.path.join(parent_dir, directory)
# Create the directory
# 'GeeksForGeeks' in
# '/home / User / Documents'
os.mkdir(path)
print("path : " + path)
print("Directory '% s' created" % directory)
return path
def smoothImagesFolder(folderName):
parentPath = "E:\\BACKBONE\\image_enhancement\\Frames\\" + folderName
totalFiles = 0
totalDir = 0
for base, dirs, files in os.walk(parentPath):
print('Searching in : ', base)
for directories in dirs:
totalDir += 1
for Files in files:
totalFiles += 1
print('Total Number of directories', totalDir)
count = totalDir + 1
# Directory
directory = "Smooth_Images" + str(count)
# Parent Directory path
parent_dir = "E:\\BACKBONE\\image_enhancement\\Frames\\" + folderName
# Path
path = os.path.join(parent_dir, directory)
# Create the directory
# 'GeeksForGeeks' in
# '/home / User / Documents'
os.mkdir(path)
print("path : " + path)
print("Directory '% s' created" % directory)
return path
imageEnhancement/CreateNewFolderForVideos.py
View file @ 64a584d0
# Python program to explain os.mkdir() method
# importing os module
import os import os
def createFolder(name):
def createFolderForEnhancedVideos():
parentPath = "E:\\BACKBONE\\image_enhancement\\EnhancedVideos" parentPath = "E:\\BACKBONE\\image_enhancement\\EnhancedVideos"
totalFiles = 0 totalFiles = 0
...@@ -21,22 +19,15 @@ def createFolder(name): ...@@ -21,22 +19,15 @@ def createFolder(name):
count = totalDir + 1 count = totalDir + 1
# Directory # Directory
directory = name directory = "EnhancedVideo" + str(count)
# Parent Directory path
parent_dir = "E:\\BACKBONE\\image_enhancement\\EnhancedVideos\\"
# Path # Path
path = os.path.join(parent_dir, directory) path = os.path.join(parentPath, directory)
# Create the directory # Create the directory
# 'GeeksForGeeks' in # 'GeeksForGeeks' in
# '/home / User / Documents' # '/home / User / Documents'
os.mkdir(path) os.mkdir(path)
print("path : " + path)
print("Directory '% s' created" % directory) print("Directory '% s' created" % directory)
return directory return path
if __name__ == '__main__':
# Calling the function
createFolder()
imageEnhancement/EnhaceFramesUsingUnsharpMasking.py
View file @ 64a584d0
import cv2 as cv2 import cv2 as cv2
import numpy as np
import os import os
import matplotlib.pyplot as plt import matplotlib.pyplot as plt
...@@ -20,13 +19,9 @@ def enhanceFrames(folderName, rate): ...@@ -20,13 +19,9 @@ def enhanceFrames(folderName, rate):
for file in os.listdir(path): for file in os.listdir(path):
if file.endswith(".jpg"): if file.endswith(".jpg"):
image = cv2.imread(path + "\\" + file) image = cv2.imread(path + "\\" + file)
# print(image)
# print("file : " + file)
gaussian_3 = cv2.GaussianBlur(image, (0, 0), 3.0) gaussian_3 = cv2.GaussianBlur(image, (0, 0), 3.0)
unsharp_image = cv2.addWeighted(image, 5, gaussian_3, -3.5, 0, image) unsharp_image = cv2.addWeighted(image, 5, gaussian_3, -3.5, 0, image)
cv2.imwrite("E:\\BACKBONE\\image_enhancement\\Frames\\"+folderName+"\\"+enhancedPath+"\\%d.jpg" % count, unsharp_image) cv2.imwrite("E:\\BACKBONE\\image_enhancement\\Frames\\"+folderName+"\\"+enhancedPath+"\\%d.jpg" % count, unsharp_image)
# cv2.waitKey(0)
# cv2.destroyAllWindows()
count += 1 count += 1
value = FramesToVid.generate_video(folderName, enhancedPath, rate) value = FramesToVid.generate_video(folderName, enhancedPath, rate)
......
imageEnhancement/FramesToVid.py
View file @ 64a584d0
...@@ -3,25 +3,19 @@ import os ...@@ -3,25 +3,19 @@ import os
import cv2 import cv2
from PIL import Image from PIL import Image
# Video Generating function # Video Generating function
from imageEnhancement import CreateNewFolderForVideos from imageEnhancement import CreateNewFolderForVideos
def generate_video(folderName, enhancedPath, rate): def generate_video(folderName, parentFolder, rate):
print("folder name : "+folderName) print("Image folder : " + folderName)
print("enhancedPath : "+enhancedPath) print("parentFolder : " + parentFolder)
video_folder_name = "video_"+folderName video_folder_name = "video_" + folderName.split('\\')[5]
CreateNewFolderForVideos.createFolder(video_folder_name)
# Checking the current directory path video_folder_path = CreateNewFolderForVideos.createFolderForEnhancedVideos()
#print(os.getcwd())
# Folder which contains all the images # path = "E:\\BACKBONE\\image_enhancement\\Frames\\"+folderName+"\\"+enhancedPath
# from which video is to be generated path = folderName
#os.chdir("E:\\#ProgrammingWork\\Python\\VideoEnhance\\Frames\\"+folderName)
path = "E:\\BACKBONE\\image_enhancement\\Frames\\"+folderName+"\\"+enhancedPath
mean_height = 0 mean_height = 0
mean_width = 0 mean_width = 0
...@@ -44,9 +38,6 @@ def generate_video(folderName, enhancedPath, rate): ...@@ -44,9 +38,6 @@ def generate_video(folderName, enhancedPath, rate):
mean_width = int(mean_width / num_of_images) mean_width = int(mean_width / num_of_images)
mean_height = int(mean_height / num_of_images) mean_height = int(mean_height / num_of_images)
# print(mean_height)
# print(mean_width)
# Resizing of the images to give # Resizing of the images to give
# them same width and height # them same width and height
for file in os.listdir('.'): for file in os.listdir('.'):
...@@ -65,10 +56,12 @@ def generate_video(folderName, enhancedPath, rate): ...@@ -65,10 +56,12 @@ def generate_video(folderName, enhancedPath, rate):
print(im.filename.split('\\')[-1], " is resized") print(im.filename.split('\\')[-1], " is resized")
# --------------------------------------------------------------------------------------------------------------- # ---------------------------------------------------------------------------------------------------------------
image_folder = 'E:\\BACKBONE\\image_enhancement\\Frames\\'+folderName+'\\'+enhancedPath # make sure to use your folder image_folder = folderName
video_name = 'video_'+folderName+'.avi' print("imagefolder ", image_folder)# make sure to use your folder
print("video folder path ", video_folder_path)# make sure to use your folder
video_name = 'Enhanced_Video.avi'
os.chdir("E:\\BACKBONE\\image_enhancement\\EnhancedVideos\\"+video_folder_name) os.chdir(video_folder_path)
images = [img for img in os.listdir(image_folder) images = [img for img in os.listdir(image_folder)
if img.endswith(".jpg") or if img.endswith(".jpg") or
...@@ -85,7 +78,7 @@ def generate_video(folderName, enhancedPath, rate): ...@@ -85,7 +78,7 @@ def generate_video(folderName, enhancedPath, rate):
# the width, height of first image # the width, height of first image
height, width, layers = frame.shape height, width, layers = frame.shape
video = cv2.VideoWriter(video_name, 0, rate, (width, height)) video = cv2.VideoWriter(video_name, cv2.VideoWriter_fourcc(*'MP4V'), rate, (width, height))
# Appending the images to the video one by one # Appending the images to the video one by one
for image in images: for image in images:
...@@ -94,5 +87,5 @@ def generate_video(folderName, enhancedPath, rate): ...@@ -94,5 +87,5 @@ def generate_video(folderName, enhancedPath, rate):
# Deallocating memories taken for window creation # Deallocating memories taken for window creation
# cv2.destroyAllWindows() # cv2.destroyAllWindows()
# video.release() # releasing the video generated # video.release() # releasing the video generated
return video_folder_name+"\\"+video_name print(video_folder_path.split('\\')[4])
return video_folder_path.split('\\')[4]
\ No newline at end of file
imageEnhancement/ImageSharpening.py 0 → 100644
View file @ 64a584d0
import cv2
import numpy as np
import os
from imageEnhancement import CreateNewFolderForFrames
from imageEnhancement import RemoveGaussianNoise
def imageSharp(parentFolder, ContrastAdjustedFolder, rate):
SharpImages = CreateNewFolderForFrames.createFolderForSharpImages(parentFolder)
count = 10000000
for file in os.listdir(ContrastAdjustedFolder):
if file.endswith(".jpg"):
image = cv2.imread(ContrastAdjustedFolder + "\\" + file)
kernel_sharpening = np.array([[-1, -1, -1],
[-1, 9, -1],
[-1, -1, -1]])
# applying the sharpening kernel to the input image & displaying it.
sharpened = cv2.filter2D(image, -1, kernel_sharpening)
cv2.imwrite(SharpImages + "\\%d.jpg" % count, sharpened)
count += 1
value = RemoveGaussianNoise.removeGaussianNoise(parentFolder, SharpImages, rate)
return value
imageEnhancement/RemoveGaussianNoise.py 0 → 100644
View file @ 64a584d0
import cv2
import os
from imageEnhancement import CreateNewFolderForFrames, FramesToVid
from imageEnhancement import Smooth
def removeGaussianNoise(parentFolder, SharpImages, rate):
GaussianDenoised = CreateNewFolderForFrames.DenoiseGaussian(parentFolder)
count = 10000000
for file in os.listdir(SharpImages):
if file.endswith(".jpg"):
img = cv2.imread(SharpImages + "\\" + file)
dst = cv2.fastNlMeansDenoisingColored(img, None, 10, 10, 7, 5)
cv2.imwrite(GaussianDenoised + "\\%d.jpg" % count, dst)
count += 1
# Smooth.imageSmooth(parentFolder, GaussianDenoised)
value = FramesToVid.generate_video(GaussianDenoised, parentFolder, rate)
return value
imageEnhancement/Smooth.py 0 → 100644
View file @ 64a584d0
import cv2
import os
from imageEnhancement import CreateNewFolderForFrames
def imageSmooth(parentFolder, GaussianDenoised):
smooth = CreateNewFolderForFrames.smoothImagesFolder(parentFolder)
count = 10000000
for file in os.listdir(GaussianDenoised):
if file.endswith(".jpg"):
img = cv2.imread(GaussianDenoised + "\\" + file)
blur = cv2.bilateralFilter(img, 60, 90, 90)
cv2.imwrite(smooth + "\\%d.jpg" % count, blur)
count += 1
# if __name__ == '__main__':
# imageSmooth("Frames1", "E:\\BACKBONE\\image_enhancement\\Frames\\Frames1\\Sharp_Frames2")
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