PyImageSearch

FEBRUARY 6, 2023

The Vegetable Image Dataset comprises 15 vegetable images, with 224×224 color images of 21,000 different vegetables from 15 categories and 1400 images per category. Figure 2 shows 9 of the 15 vegetable image categories from the dataset. Figure 2: Analyzing a few categories from the vegetable image classification dataset.

Auto-classification 144

Auto-classification Computer Vision Neural Network Deep Learning 144

Heartbeat

FEBRUARY 13, 2023

In addition, Kangas is designed to operate in any environment, whether locally on a laptop or as a stand-alone program, making it a versatile tool that can adapt to different needs and use cases. Grouped by the category We can also filter the data based on different conditions.

Data Science 94

Data Science Python Deep Learning Data Scientist 94

Unite.AI

AUGUST 19, 2023

Here is a look at some of the best features of Jasper: More than 11,000 free fonts and 2,500 categories of writing styles Supports 25+ languages Intuitive interface Long-form writing assistant (1,000+ words) Identify key elements in text (pronouns, verbs, names, etc.) Also see how Jasper compares against leading AI writing generators.

AI Tools 240

AI Tools AI AI Artificial Intelligence 240

Mlearning.ai

SEPTEMBER 4, 2023

It’s like picking the juiciest apples from the orchard.isin() Magic: Select rows matching specific categories effortlessly. Example: Imagine you have a dataset of product names, and you want to extract products that contain the word ‘premium’ in their names. str.contains('phone', case=False)] print(filtered_data) 4.

Python 52

Python Categorization Machine Learning Data Analysis 52

Unite.AI

JULY 14, 2023

Categories include: Coaches & Teaching YouTube Creators & Bloggers Course Creators & Social Media Managers Marketers & Agencies Pictory Test To provide you with a thorough evaluation of Pictory, I put each feature to the test. Pictory is best used on a desktop or laptop computer. Can I use Pictory on my phone?

AI 246

AI AI Auto-complete AI Tools 246

O'Reilly Media

AUGUST 8, 2023

Although large language models clearly fall into the category of NLP, we suspect that most users associate NLP with older approaches to building chatbots. Most of these alternatives descend from Meta’s LLaMA and Georgi Gerganov’s llama.cpp (which can run on laptops, cell phones, and even Raspberry Pi).

ChatGPT 72

ChatGPT Large Language Models Machine Learning LLM 72

PyImageSearch

JANUARY 9, 2023

✓ Access on mobile, laptop, desktop, etc. Thus, practical applications demand the development of models that are robust to nuisances and can generalize to novel unseen views or depictions of an object.

Computer Vision 103

Computer Vision Deep Learning Neural Network Algorithm 103

Flipboard

JULY 31, 2023

Image classification involves assigning a label to an image from a predetermined set of categories. For instance, the machine learning model aims to accurately determine whether the image is of a cat, dog, or bird in an image classification task with those categories. So, what makes semantic segmentation unique?

Machine Learning 104

Machine Learning Computer Vision Deep Learning Convolutional Neural Networks 104

Google Research AI blog

MARCH 23, 2023

robot.move_to_left('counter') robot.move_in_between('sink', 'oven') pos1 = robot.get_pos('sofa') pos2 = robot.get_pos('table') for i in range(2): robot.move_to(pos1) robot.move_to(pos2) # move 2 meters north of the laptop, then move 3 meters rightward.

Robotics 114

Robotics Cognitive Map 114

Unite.AI

OCTOBER 25, 2023

You can enhance video quality by connecting FineShare to your phone's camera, DSLR, webcam, or laptop camera. With FineCam, you can use whatever camera you have on hand as your webcam (DSLR, webcam, laptop camera, phone camera, etc.) It's nice that FineShare has these categories as suggestions to give me ideas.

AI 264

AI AI AI Tools Algorithm 264

The MLOps Blog

JANUARY 5, 2023

What I see as a problem in the marketplace like you would, let’s say, eBay or whatever the problem that you might face there is that the number of categories is not constant. In the case of a new category, you wouldn’t support it right away. Then we have one image that is associated with a new category.

Computer Vision 52

Computer Vision Machine Learning ML Explainability 52

PyImageSearch

JUNE 12, 2023

Think of it as finding the best way to match items from two categories, like connecting workers to jobs or students to projects. Each item from one category is paired with at most one item from the other category, and the cost of the pairs is optimal. ✓ Access on mobile, laptop, desktop, etc.

Algorithm 60

Algorithm Computer Vision Deep Learning Artificial Intelligence 60

Dlabs.ai

MAY 17, 2021

NVIDIA Blog & NVIDIA Developer (Developers/Business) NVIDIA is like royalty in the tech sector: the company invented the GPU, which creates interactive graphics on laptops, workstations, mobile devices, notebooks, PCs, and more — and the company shares how it all works across these two sites.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence AI Tools Machine Learning 52

Heartbeat

APRIL 18, 2023

VGG Neural Network Architecture —  Source The convolutional layers are responsible for extracting features from the input image, while the fully connected layers are responsible for classifying the image into different categories. Import the library [link] Dataset This article’s dataset includes 15 distinct categories of human activities.

Convolutional Neural Networks 52

Convolutional Neural Networks Deep Learning Neural Network Machine Learning 52

PyImageSearch

SEPTEMBER 25, 2023

Categorial features can be binary (e.g., Objectives can be categorized into two categories: Engagement level objectives include clicks, watches, intensity of watch, etc. ✓ Access on mobile, laptop, desktop, etc. Hence, the ranking network takes in many more features describing the video (e.g.,

Computer Vision 120

Computer Vision Deep Learning Neural Network Algorithm 120

O'Reilly Media

NOVEMBER 28, 2023

A few have even tried out Bard or Claude, or run LLaMA 1 on their laptop. Some can easily be run on a laptop or even in a web browser. The LLaMA-family models also fall into the “so-called open source” category that restricts what you can build. Generative AI has been the biggest technology story of 2023.

Generative AI 108

Generative AI AI AI Data Analysis 108

Snorkel AI

APRIL 13, 2023

First, with local training, Jenna can train that model only on her own data, her own laptop. The main idea is to assemble users who are interested in the same task, pull their data to train the model, and the key feature is that the model is actually trained without Jenna’s data ever leaving her laptop. She’s good to go.

Machine Learning 52

Machine Learning OpenAI ML BERT 52

Snorkel AI

APRIL 13, 2023

First, with local training, Jenna can train that model only on her own data, her own laptop. The main idea is to assemble users who are interested in the same task, pull their data to train the model, and the key feature is that the model is actually trained without Jenna’s data ever leaving her laptop. She’s good to go.

Machine Learning 52

Machine Learning OpenAI ML BERT 52

PyImageSearch

JUNE 26, 2023

Meanwhile, the linear layer predicts the class label using a softmax function , which helps determine the most probable category for each object. ✓ Access on mobile, laptop, desktop, etc. Figure 6: Feed-Forward Prediction Heads highlighted in the entire DETR architecture (source: image provided by the authors).

Convolutional Neural Networks 103

Convolutional Neural Networks Computer Vision Neural Network Deep Learning 103

PyImageSearch

AUGUST 7, 2023

course difficulty, category, and skills). course difficulty, course category, and course skills, etc.). ✓ Access on mobile, laptop, desktop, etc. course difficulty, course category, and course skills, etc.). skills and industry) and course metadata (e.g., skills, industry, etc.) and course-level features (e.g.,

Computer Vision 98

Computer Vision Neural Network Deep Learning Algorithm 98

PyImageSearch

MARCH 13, 2023

However, background pixels such as sky and road are often disregarded as object categories in instance segmentation tasks. As described in the Scene Parsing dataset page , the instance annotation masks are stored in RGB image format and structured as follows: The R(ed) channel encodes category ID. the split sky segments). .

Computer Vision 117

Computer Vision Deep Learning Neural Network Metadata 117

PyImageSearch

JANUARY 8, 2024

How can we tackle this simple problem and enhance our model so that it not only correctly predicts categories on original images but also on sketches and cartoons of cats and dogs? ✓ Access on mobile, laptop, desktop, etc. We wanted to test it on sketches and cartoons of cats and dogs at inference.

Computer Vision 64

Computer Vision Neural Network Deep Learning Artificial Intelligence 64

PyImageSearch

NOVEMBER 6, 2023

Finding Unique Mask Values ( Lines 59-62 ) For segmentation tasks, each pixel in a mask corresponds to a particular class or category. These unique values represent the different classes/categories in the segmentation masks. ✓ Access on mobile, laptop, desktop, etc.

Computer Vision 67

Computer Vision Neural Network Deep Learning Categorization 67

PyImageSearch

SEPTEMBER 18, 2023

Suppose we have an image I with multiple objects, and we want to classify each object in the image into a set of categories in a zero-shot way (i.e., ✓ Access on mobile, laptop, desktop, etc. Let us now take an example and understand how our SAM+CLIP system can help us perform complex and diverse downstream tasks.

Computer Vision 67

Computer Vision Deep Learning AI AI 67

PyImageSearch

OCTOBER 2, 2023

Furthermore, there’s a diverse representation across classes, ensuring distinct visual differences between categories, such as between sneakers and ankle boots. ✓ Access on mobile, laptop, desktop, etc. Figure 6: Fashion-MNIST images reconstructed by Variational Autoencoder after training (source: image by the author).

Computer Vision 120

Computer Vision Deep Learning Neural Network Auto-complete 120

Explosion

MARCH 17, 2019

If you’ve been using our annotation tool Prodigy , you might recognize this format from the pattern files you can load in to bootstrap new entity types and text categories. If you can’t easily make your desktop, your colleague’s laptop and your server all run the same code, you’re going to have a bad time. average was 2 lbs.")

NLP 52

NLP Python Neural Network Natural Language Processing 52

PyImageSearch

FEBRUARY 12, 2024

safety_settings pertain to content filtering thresholds for categories like harassment and hate speech. ✓ Access on mobile, laptop, desktop, etc. The default generation_config includes parameters like temperature, top_p , top_k , and max_output_tokens , influencing the model’s content generation.

Computer Vision 64

Computer Vision Python Deep Learning ChatGPT 64

PyImageSearch

SEPTEMBER 11, 2023

CLIP is prompted with hand-engineered text prompts to enhance its zero-shot classification performance on object categories, etc. ✓ Access on mobile, laptop, desktop, etc. For example, engineered text prompts are used to query ChatGPT and get a useful or desirable response for the user.

Computer Vision 117

Computer Vision AI AI Prompt Engineer 117

PyImageSearch

DECEMBER 19, 2022

✓ Access on mobile, laptop, desktop, etc. For that, we will move on to the utils.py script located in the pyimagesearch directory. putText( frame, labelMap[detection.label], ( bbox[0] + 10, bbox[1] + 20, ), cv2.FONT_HERSHEY_TRIPLEX, FONT_HERSHEY_TRIPLEX, 0.5, color, ) cv2.putText( FONT_HERSHEY_TRIPLEX, 0.5, color, ) cv2.rectangle(frame,

Neural Network 52

Neural Network Computer Vision Deep Learning Metadata 52

PyImageSearch

JULY 17, 2023

Figure 7 : Visualization of the Latent Space for the Test Dataset, Colored by Clothing Category (source: image by the author). For example, the orange cloud of points in the top right corner of the latent space are all different images of trousers, and the blue cloud of points toward the center top are all T-shirt/top categories.

Computer Vision 98

Computer Vision Deep Learning Python Machine Learning 98

The MLOps Blog

JUNE 27, 2023

You can effortlessly scale any workload or application from a laptop to the cloud without the cost or expertise required to build complex infrastructure. Some popular MLOps tools for compute and infrastructure in 2023 Ray Open Source Anyscale is the developer of Ray , a unified compute framework for scalable computing.

Machine Learning 134

Machine Learning Metadata Data Quality Data Scientist 134

Ines Montani

FEBRUARY 16, 2024

If you’re looking for interesting fonts for slide titles, the “Display” category is a good one to start browsing through, and you can also define more fine-grained filtering. The site also provides a handy glossary that explains all relevant font terminology.

Explainability 144

Explainability 144

Topbots

APRIL 28, 2023

For example, a “laptop” can be used as a “plate”, as a “body shield”, or as “wall art” [ 4 ]. laptop”) and the use case word (e.g. Unlike the Remote Associations Test, this test measures divergent thinking, meaning that there is no right answer. Then, I used cosine distance between the two embeddings to calculate the semantic distance.

Large Language Models 52

Large Language Models Natural Language Processing Robotics Explainability 52

John Snow Labs

JULY 19, 2023

Community contributions include projects like LLaVA-MPT, which incorporates vision understanding into MPT, GGML, which optimizes MPT for Apple Silicon and CPUs, and GPT4All, enabling users to run GPT4-like chatbots on their laptops using MPT as a backend model.

LLM 98

LLM OpenAI Large Language Models NLP 98