Muhammad Hanzla@muhammad_hanzla_451
is under improvement
7
Events attended
2
Submissions made
Leetcode problem solver
Pakistan
1 year of experience
About me
Hello! this is Hanzla, a student of computer science in the Government College University Faisalabad.I have solved over 200 LeetCode questions using Python and Java. I am passionate about AI and am also learning full-stack development. In this journey, I have learned HTML, CSS, and JavaScript, and I am currently learning React and other technologies. I have also completed a couple of projects using C++, HTML, CSS, and JavaScript in web development. Additionally, I have been a trainer for Data Structures and Algorithms (DSA) and LeetCode at iCodeGuru for the past few months.
is under improvement
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🤓 Submissions
Image Object Detection Web App
The Object Detector Web App is an innovative and versatile application that enables users to detect and classify objects within images effortlessly. Developed using the Streamlit framework, this web app harnesses the power of advanced machine learning algorithms, providing robust and real-time object detection capabilities. The user interface is designed to be intuitive and user-friendly, allowing individuals with little to no technical background to navigate and use the app with ease. Upon accessing the app, users can upload their images through a straightforward upload interface. Once an image is uploaded, the app processes it in real-time, highlighting and labeling detected objects within the image. Each detected object is accompanied by a bounding box and a label indicating the object's class and, optionally, a confidence score that reflects the model's certainty in its prediction. One of the standout features of the Object Detector Web App is its flexibility and adaptability. It can be customized and extended to suit various use cases, whether for educational purposes, research, or commercial applications. For instance, businesses can utilize the app for inventory management by detecting and categorizing products in real-time, while researchers can use it to analyze and annotate large datasets. In summary, the Object Detector Web App is a comprehensive and powerful tool that democratizes access to advanced object detection technology. By combining cutting-edge machine learning models with an easy-to-use interface, it empowers users to perform complex image analysis tasks with minimal effort, making it an invaluable resource across various domains.
Collaborative Summarizer
Students and researchers face immense digital content, leading to digital eye strain and cognitive overload. The constant strain not only affects health but also hampers comprehension and retention, making efficient reading essential for maintaining productivity and well-being. Our team proudly present you with a powerful text summarization tool designed to condense extensive text into concise summaries, saving you time and enhancing comprehension. We have employed the powerful model of Llama 3 along with the frameworks of Streamlit, torch, PyPDF2 and transformers. It Supports direct text input or PDF uploads for summarization. Our app Utilizes advanced algorithms from Llama 3 to ensure accurate and context-aware summaries. Text summarization tools are gaining traction as essential aids in educational, corporate, and research sectors. Furthermore, the increasing demand for efficient reading tools amongst academics, professionals, and students is expanding its scope. One of the major strengths of our app is that it saves time on reading, supports collaborative learning and work. Weakness is that our text summarizer depends on the quality of input text for optimal output. Expanding usage in educational technologies and corporate knowledge management has increased the scope of our tool. However, High competition with existing summarization and reading assistance tools is a challenge for us to keep improving. One of the major areas of improvement is that the file upload limit is 200MB and we can improve it so that multiple files or zip folders can be uploaded to get the desired result.
