Error: Traceback (most recent call last):
File “D:\Attendance_System_Us\main.py”, line 10, in <module>
faceloc = face_recognition.face_locations(imgModi)[0]
File “D:\Attendance_System_Us\venv\lib\site-packages\face_recognition\api.py”, line 121, in face_locations
return [_trim_css_to_bounds(_rect_to_css(face), img.shape) for face in _raw_face_locations(img, number_of_times_to_upsample, model)]
File “D:\Attendance_System_Us\venv\lib\site-packages\face_recognition\api.py”, line 105, in _raw_face_locations
return face_detector(img, number_of_times_to_upsample)
RuntimeError: Unsupported image type, must be 8bit gray or RGB image.

Solutions :

uninstall numpy >=2

1. pip uninstall numpy
2. pip install numpy==1.25.1

Thank You :)

These are top blockchain projects with code, documents and video. These are very Interested, trending and best blockchain projects .

1. Blockchain Voting System

2. Blockchain Decentrilzed Blog Project

3. Fake Product Identification using blockchain

4. Blockchain Evidence Management Project

5. Decentrilzed Money Transaction Blockchain Project

6. Land Registry using Blockchain

7. Blood Bank Management through Blockchain

8. Health Records using Blockchain

9. NGO fund raising using blockchain technology

10. Ethereum Explorer Clone Project

More Blockchain Projects : https://youtube.com/playlist?list=PL5g-9zkOohaHP72df1JO6Jqn1K5mM3rM9&si=dn8-wpK5WzmCjDHH

Contact us for the Project Code and documents with Video turorials

Mail : vatshayan007@gmail.com

Website : https://www.finalproject.in/

Youtube Channel : https://www.youtube.com/@computerscienceproject

Issue you may be facing (example):

C:\Users\User\AppData\Local\Programs\Python\Python311\Lib\site-packages\sklearn\base.py:348: InconsistentVersionWarning: Trying to unpickle estimator DecisionTreeClassifier from version 1.2.2 when using version 1.3.2. This might lead to breaking code or invalid results. Use at your own risk. For more info please refer to:
https://scikit-learn.org/stable/model_persistence.html#security-maintainability-limitations
warnings.warn(
Traceback (most recent call last):
File “c:\Users\User\Downloads\malware-main 2–20231217T100622Z-001\malware-main 2\app.py”, line 7, in <module>
model = joblib.load(“malware_model.pkl”)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File “C:\Users\User\AppData\Local\Programs\Python\Python311\Lib\site-packages\joblib\numpy_pickle.py”, line 658, in load
obj = _unpickle(fobj, filename, mmap_mode)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File “C:\Users\User\AppData\Local\Programs\Python\Python311\Lib\site-packages\joblib\numpy_pickle.py”, line 577, in _unpickle
obj = unpickler.load()
^^^^^^^^^^^^^^^^
File “C:\Users\User\AppData\Local\Programs\Python\Python311\Lib\pickle.py”, line 1213, in load
dispatch[key[0]](self)
File “C:\Users\User\AppData\Local\Programs\Python\Python311\Lib\site-packages\joblib\numpy_pickle.py”, line 402, in load_build
Unpickler.load_build(self)
File “C:\Users\User\AppData\Local\Programs\Python\Python311\Lib\pickle.py”, line 1718, in load_build
setstate(state)
File “sklearn\tree\tree.pyx”, line 728, in sklearn.tree._tree.Tree.setstate_
File “sklearn\tree\_tree.pyx”, line 1434, in sklearn.tree._tree._check_node_ndarray
ValueError: node array from the pickle has an incompatible dtype:
- expected: {‘names’: [‘left_child’, ‘right_child’, ‘feature’, ‘threshold’, ‘impurity’, ‘n_node_samples’, ‘weighted_n_node_samples’, ‘missing_go_to_left’], ‘formats’: [‘<i8’, ‘<i8’, ‘<i8’, ‘<f8’, ‘<f8’, ‘<i8’, ‘<f8’, ‘u1’], ‘offsets’: [0, 8, 16, 24, 32, 40, 48, 56], ‘itemsize’: 64}
- got : [(‘left_child’, ‘<i8’), (‘right_child’, ‘<i8’), (‘feature’, ‘<i8’), (‘threshold’, ‘<f8’), (‘impurity’, ‘<f8’), (‘n_node_samples’, ‘<i8’), (‘weighted_n_node_samples’, ‘<f8’)]

Solution :

Directly Run this Command on your VSC Terminal.

pip install scikit-learn==1.2.2

Now run your project code or [python app.py] command and enjoy !!

Thank you :)

1. Diabetes Prediction System
2. Co2 Emission Prediction System
3. Data Depublication Removal System
4. Android Malware Detection System
5. Rainfall prediction System
6. Movie Recommendation System
7. Fake News Detection System
8. Stock Price Prediction System
9. Malware Analysis System
10. Network Intrusion Detection

More Machine Learning Projects :

Code, PPT, Synopsis, Report and Explanation Video HD is available for above projects.

Contact :

💬 Mail : vatshayan007@gmail.com

💬 Whatsapp : +91 9310631437 : [Chat]

Website : https://www.finalproject.in

Open Terminal on visual studio code.

Give commands :

pip install virtualenv

virtualenv venv

source venv/bin/activate

your virtual environment is setup, now you can easily run python, flask, django or any python projects.

Still any queries ?

Mail : vatshayan007@gmail.com

Just give command on terminal :

python3 -m pip install scikit-learn

More Queries / Problems ?
Need Solution : vatshayan007@gmail.com

Website : https://www.finalproject.in

1. Blockchain Communication Project

2. Blockchain Voting System Project

3. ImageChain Blockchain Project

4. Record Ledger Blockchain Project

5. Money Transcation Blockchain Project

More Blockchain Projects : https://vatshayan.medium.com/top-10-final-year-blockchain-projects-d3a9753464e7

Youtube Blockchain Project Playlist : https://www.youtube.com/playlist?list=PL5g-9zkOohaHP72df1JO6Jqn1K5mM3rM9

For Code, Report, synopsis and PPT of above Projects please mail me.

If you need help on Blockchain Projects then contact me-

📫 HOW TO REACH ME FOR PROJECT HELP

💬 WhatsApp: +91 9310631437 (Helping 24*7)

WhatsApp Message Link : https://wa.me/9310631437

💬 Mail: vatshayan007@gmail.com

💬 Website: https://www.finalproject.in/

Thank you 🙏

1. Blockchain Voting System

2. Money Transaction Storing Project

3. Blockchain Communication System Project

More Blockchain Projects : https://vatshayan.medium.com/top-10-final-year-blockchain-projects-d3a9753464e7

Youtube Blockchain Project Playlist : https://www.youtube.com/playlist?list=PL5g-9zkOohaHP72df1JO6Jqn1K5mM3rM9

For Code, Report, synopsis and PPT of above Projects please mail me.

If you need help on Blockchain Projects then contact me-

📫 HOW TO REACH ME FOR PROJECT HELP

💬 WhatsApp: +91 9310631437 (Helping 24*7)

WhatsApp Message Link : https://wa.me/9310631437

💬 Mail: vatshayan007@gmail.com

💬 Website: https://www.finalproject.in/

Thank you 🙏

Blockchain is a shared, immutable register for recording transactions, tracking assets and building trust between parties involved. Blockchain posses many advantages and it will gonna rule IT in future especially finance, security and supply chain.

Here is path as step by step to follow to get skilled in blockchain.

Origin and working of Blockchain

• How does our current financial system work?
• What can be the possible solution?
• What is a distributed system?
• What is Blockchain?
• How does Blockchain work?
• Properties of Blockchain
• Evolution of Blockchain

Basic Crypto primitives

• Hash functions
• Puzzle friendly Hash
• Collison resistant hash
• Digital signatures
• Public key crypto

Introduction to Ethereum

• What is Ethereum?
• Introducing Smart Contracts
• Cryptocurrency in Ethereum
• Mining in Ethereum
• Consensus Mechanism in Ethereum
• Platform Functions used in Ethereum
• Technologies that support Ethereum
• Ethereum Programming Language
• Components for development of Ethereum D-Apps
• Editors and tools
• Frontend Development
• Ethereum Test Networks
• ERC Tokens

Basic Solidity

• Introducing Solidity
• Sample Code
• The layout of Source File
• Structure of a Contract
• State Variables
• Functions Types
• Reference Types
• Units
• Special Variables and Functions
• Expressions and Control Structures
• Function Calls
• Error Handling
• Visibility for Functions and State Variables

Advance Solidity

• State Modifiers
• Inheritance
• Constructors
• Libraries
• Importing Smart Contracts
• Events and Logging
• Error Handling and Exceptions
• Common Pitfalls
• Gas Limit and Loops
• Sending and Receiving Ether
• Recommendations
• Contract ABI
• Setting up the development environment

Cryptocurrency and Blockchain

• Anonymity and Pseudonymity in Cryptocurrency
• Programmable Money
• What is inside a block?
• Hash Functions and Merkle Trees
• Components of Blockchain Ecosystem
• Cryptography and Consensus Algorithms
• Types of Blockchain
• Side Chains: another type of Blockchain
• Blockchain Implementations
• Blockchain Platforms

Developing A D-App Using Truffle

• Developing a D-App, Compile and Deploy the Smart Contract
• Publish the D-App, Connecting to D-App
• Ganache Output for Transaction Migration

Create And Deploy Your Private Blockchain On Multichain

• What Is Multichain?
• Privacy and Permissions in Multichain
• Mining in Multichain
• Multiple configurable Blockchains using Multichain
• Setting up a Private Blockchain

Some Certification to learn :

Basic (FREE ):

1. https://www.mygreatlearning.com/academy/learn-for-free/courses/blockchain-basics
2. https://www.udemy.com/course/blockchain-theory-101/

Advanced & Best (Paid) :

1. https://www.udemy.com/course/blockchain-developer/
2. https://www.udacity.com/course/blockchain-developer-nanodegree--nd1309
3. https://www.blockchain-council.org/blockchain-certification/
4. https://intellipaat.com/blockchain-training-course/
5. https://www.edureka.co/blockchain-training
6. https://www.simplilearn.com/blockchain-certification-training-course

Hope this help you. I have summarised and shared Important topics as Syllabus to became Blockchain Master.

If you like this article, Please like and share as it will help many.

If you need any guidance and help let me know!

Thank you :)

Abstract:

Face Detection System

This research paper gives an ideal way of detecting and recognizing human faces using OpenCV, and python which is part of Machine learning. This report contains the ways in which Machine learning, an important part of the computer science field can be used to determine the face using several libraries in OpenCV along with python. This System will contain a proposed system which will help in detecting the human face in real time. This implementation can be used at various platforms in machines and smartphones, and several software applications.

Automatic Attendance through Face recognition system

The management of the attendance can be a great burden on the teachers if it is done by hand. To resolve this problem, a smart and auto attendance management system is being utilised. By utilising this framework, the problem of proxies and students being marked present even though they are not physically present can easily be solved. This system marks the attendance using a live video stream. The frames are extracted from video using OpenCV. The main implementation steps used in this type of system are face detection and recognizing the detected face, for which dlib is used. After these, the connection of recognized faces ought to be conceivable by comparing with the database containing student’s faces. This model will be a successful technique to manage the attendance of students.

Lung cancer detection

Lung Cancer detection at an earlier stage has become a very important and needy one for a human being. Early detection helps several patients with the best chance of recovery. Timely diagnosis and determination to the type of lung cancer has important clinical significance. The features which are used for the detection of Lung Cancer are collected from the Computed Tomography (CT scan) images. Input as sympotoms will be given and output will tell that person have cancer or not. Machine Learning is an emerging technique that allows us to increase the accuracy of the result. In this project, we have implemented cancer detection using ML.

Potato disease detection

The world population is increasing at a rapid rate, and so is the demand for food. With the advancements in agricultural technology, combined with the use of artificial intelligence to predict diseases in crops, it becomes important to make relevant research to ensure sustainable agricultural development. Agriculture is the cultivation of land and raising of crops to produce food. It is a form of subsistence farming that has been practised for thousands of years. With the advancement in technology and the use of artificial intelligence in diagnosing plant diseases, it becomes important to make pertinent research toward sustainable agricultural development. In the past, diagnosis of plant diseases was done by observing the symptoms of a diseased plant. However, with the advent of artificial intelligence and its application to agriculture, it has become important to make pertinent research in this area. With the use of image processing and deep learning algorithms, it is now possible to diagnose a plant disease by using a picture taken from a smartphone. The advancement of agricultural technology has made it possible to grow more crops with limited resources. Potato is one of the staple foods that are widely consumed, becoming the 4th staple food consumed throughout the world. Also, the world demand for potato is increasing significantly, primarily due to the world pandemic coronavirus. However, potato diseases are the leading cause of the decline in the quality and quantity of the harvest. Inappropriate classification and late detection of the disease’s type will drastically worsen the plant conditions. Fortunately, several diseases in potato plants can be identified based on leaf conditions. However, the increase in the population of the world is constantly increasing the demand for more food. One way to meet this demand is to use artificial intelligence in diagnosing plant diseases and using that information to more efficiently grow food. Machine Learning as Deep Learning is applied for the work done.

Email spam detection

Email Spam has become a major problem nowadays, with Rapid growth of internet users, Email spams are also increasing. People are using them for illegal and unethical conducts, phishing and fraud. Sending malicious links through spam emails which can harm our system and can also seek in into your system. Creating a fake profile and email account is much easier for the spammers, they pretend like a genuine person in their spam emails, these spammers target those people who are not aware about these frauds. So, it is necessary to Identify those spam mails which are fraudulent. This project will identify spam by using techniques of machine learning, this project will discuss the machine learning algorithms and apply all these algorithms on our data sets and the best algorithm is selected for the email spam detection having best precision and accuracy.

Need Code, Documents & Explanation ?

How to Reach me :

Mail : vatshayan007@gmail.com

Website : https://www.cse-projects.com/

1000 Computer Science Projects : https://www.computer-science-project.in/