How to make good promt for AI to image

Make thesis complete from abstrack , keywords, until references abou How to make good promt for AI to image

Abstract:

As artificial intelligence (AI) continues to advance, the ability to analyze and interpret visual data is becoming increasingly important. One key aspect of this is the ability to provide good prompts for AI to analyze images effectively. In this thesis, we explore the various factors that contribute to creating a good prompt for AI to analyze images. We begin by discussing the different types of image prompts that are commonly used in AI, including natural language prompts, visual prompts, and hybrid prompts. We then delve into the characteristics of good prompts, including specificity, relevance, and clarity. Finally, we explore some of the challenges associated with creating effective prompts for AI to analyze images and propose potential solutions to these challenges.

Keywords: artificial intelligence, image analysis, image prompts, natural language prompts, visual prompts, hybrid prompts, specificity, relevance, clarity.

Introduction:

history of artificial intelligence by year:

• 1943: Warren McCulloch and Walter Pitts develop a model for artificial neurons that can process binary input.
• 1950: Alan Turing proposes the Turing Test to measure a machine's ability to exhibit intelligent behavior indistinguishable from that of a human.
• 1956: The Dartmouth Conference is held, marking the birth of AI as a field of research.
• 1959: Arthur Samuel creates the first self-learning program, a checkers-playing program that improves its performance over time.
• 1966: The Shakey robot is developed at Stanford Research Institute, which is the first robot to perceive its environment and respond accordingly.
• 1969: Shakey becomes the first robot to navigate a room on its own.
• 1973: The first commercial AI system, the R1 system, is developed by AI pioneer Edward Feigenbaum and his colleagues.
• 1985: The expert system industry reaches its peak, with companies spending hundreds of millions of dollars on AI research and development.
• 1997: IBM's Deep Blue defeats world chess champion Garry Kasparov.
• 2002: Roomba, the first successful consumer robot, is introduced.
• 2005: The DARPA Grand Challenge is held, challenging teams to build autonomous vehicles capable of navigating a course without human intervention.
• 2011: IBM's Watson defeats human champions on the quiz show Jeopardy!
• 2012: Google's DeepMind develops a neural network that learns to play video games at a superhuman level.
• 2015: AlphaGo, an AI developed by Google's DeepMind, defeats a human world champion at the ancient Chinese game of Go.
• 2018: AI-powered voice assistants, such as Amazon's Alexa and Apple's Siri, become widely available to consumers.
• 2020: AI is increasingly used in healthcare, particularly for image analysis and drug discovery, as well as for predicting and tracking the spread of diseases such as COVID-19.

Note that this is not an exhaustive list, but rather a brief overview of some of the major milestones in the development of AI.

brief history of image prompts:

• 2014: Google DeepDream was introduced, which uses a neural network to create psychedelic images based on existing images.
• 2015: The neural style transfer algorithm was introduced, which allows the style of one image to be applied to another.
• 2016: The first version of the Generative Adversarial Network (GAN) was introduced, which is capable of generating realistic images from random noise.
• 2018: Nvidia introduced the StyleGAN model, which generates high-quality, diverse images.
• 2019: OpenAI released DALL-E, a neural network capable of generating images from textual descriptions.
• 2021: OpenAI released CLIP, a neural network that can understand images and text, allowing for advanced image generation and manipulation.

It's worth noting that these developments are not necessarily sequential, and there have been many other advancements and breakthroughs in image prompt technology that have occurred over the years.

Q&A with answers about networks capable of generating images from textual descriptions:

Q: What is a network capable of generating images from textual descriptions? A: A network capable of generating images from textual descriptions is a type of neural network that uses natural language processing techniques to understand written descriptions and generates corresponding images.

Q: How does a network capable of generating images from textual descriptions work? A: A network capable of generating images from textual descriptions works by first encoding the textual description into a numerical format that the neural network can understand. The network then uses this numerical representation to generate an image that corresponds to the textual description.

Q: What are some applications of a network capable of generating images from textual descriptions? A: Some applications of a network capable of generating images from textual descriptions include generating images for e-commerce websites, generating images for virtual environments in gaming, and generating images for medical imaging.

Q: What are some challenges associated with a network capable of generating images from textual descriptions? A: Some challenges associated with a network capable of generating images from textual descriptions include accurately understanding the nuances of language, generating high-quality images that are true to the textual description, and dealing with the high dimensionality of the image data.

Q: What are some techniques used to improve the performance of a network capable of generating images from textual descriptions? A: Some techniques used to improve the performance of a network capable of generating images from textual descriptions include using attention mechanisms to focus on relevant parts of the textual description, using adversarial training to generate more realistic images, and using reinforcement learning to fine-tune the network's parameters.

The ability of artificial intelligence (AI) to analyze and interpret visual data has become increasingly important as the use of visual information grows in various industries. One key aspect of this process is the ability to provide good prompts for AI to analyze images effectively. In this thesis, we aim to investigate the various factors that contribute to creating a good prompt for AI to analyze images.

Types of Image Prompts:

There are several types of image prompts that are commonly used in AI, including natural language prompts, visual prompts, and hybrid prompts. Natural language prompts involve using text to describe the image being analyzed. Visual prompts use images or other visual stimuli to prompt analysis. Hybrid prompts combine both natural language and visual prompts to provide a more comprehensive prompt for analysis.

failed: 

Leah Gotti in beach background, adopt, anime face, detailed, high resolution, 8k, stylized anime image,

Leah Gotti with white color clothing, epic, tragic, military art, fantasy, dieselpunk, hd shot, digital portrait, pink hair, beautiful face, beautiful smiling young woman, artstation, by artgerm,   photo realistic, unreal engine 5, highly detailed, octane render

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male:

Putu Suhartawan but baby, photo hyper realistic , super high detail

Putu Suhartawan, A 1950s seemingly unconcerned that hes on fire. a photorealistic oil painting

Putu Suhartawan, photo-realistic, soft smooth lighting, polycount, modular constructivism, pop surrealism, physically based rendering, 8K

professional portrait photograph of Putu Suhartawan with elvis teal hair , gold garment ((sultry flirty look)), a handsome symmetrical face, Randy orton natural makeup, ((standing outside in bank of seoul)), stunning seoul city upscale environment, ultra realistic, concept art, elegant, highly detailed, intricate, sharp focus, depth of field, f/1.8, 85mm, medium shot, mid shot, (centered image composition), (professionally color graded), ((bright soft diffused light)), volumetric fog, trending on instagram, trending on tumblr, hdr 4k, 8k

Ironman in Combat, Aggressive, Intense, Dangerous, Dramatic, Sony Alpha a7 III, Sony FE 70-200mm f/2.8 GM OSS, Nighttime, Action Photography, Digital Film, High Realism, Continuous Shooting Mode, Shutter Priority, Contrast Boost, Dark and Moody Lighting

Futuristic, Technological, Powerful, Daring, Canon EOS 5D Mark IV, Canon EF 70-200mm f/2.8L IS II USM, Daytime, Action Photography, Digital Film, High Realism, Continuous Shooting Mode, Aperture Priority, High Dynamic Range, Cinematic Lighting, Aspect Ratio:

Hary Tanoesoedibjo as senator with white color clothing, epic, booming, politician art, fantasy, dieselpunk, hd shot, digital portrait, pink hair, young man face,  smiling young man, artstation, by artgerm,   photo realistic, unreal engine 5, highly detailed, octane render

Hary Tanoesoedibjo leading perindo party with white color clothing, epic, tragic, military art, fantasy, dieselpunk, hd shot, digital portrait, muscle man, artstation, by artgerm,   photo realistic, unreal engine 5, highly detailed, octane render 

Hary Tanoesoedibjo do job as president of indonesia, portrait, epic, tragic, military art, fantasy, dieselpunk, hd shot, digital portrait, beautiful, artstation, by artgerm,   photo realistic, unreal engine 5, highly detailed, octane render

female:

Lita WWE on entrance with white color clothing, epic, tragic, military art, fantasy, dieselpunk, hd shot, digital portrait, pink hair, beautiful face, beautiful smiling young woman, artstation, by artgerm,   photo realistic, unreal engine 5, highly detailed, octane render

 surrealism, smooth, epic details

professional portrait photograph of a gorgeous Viking queen with long wavy brown hair and black, gold garment ((sultry flirty look)), a beautiful symmetrical face, cute natural makeup, ((standing outside in snowy lake)), stunning Viking city upscale environment, ultra realistic, concept art, elegant, highly detailed, intricate, sharp focus, depth of field, f/1.8, 85mm, medium shot, mid shot, (centered image composition), (professionally color graded), ((bright soft diffused light)), volumetric fog, trending on instagram, trending on tumblr, hdr 4k, 8k

professional portrait photograph of a gorgeous Ottoman Princess with long wavy dark black hair, wearing white and red Ottoman garment, ((sultry flirty look)), a beautiful symmetrical face, cute natural makeup, ((standing outside in snowy garden)), stunning garden upscale environment, ultra realistic, concept art, elegant, highly detailed, intricate, sharp focus, depth of field, f/1.8, 85mm, medium shot, mid shot, (centered image composition), (professionally color graded), ((bright soft diffused light)), volumetric fog, trending on instagram, trending on tumblr, hdr 4k, 8k

a catgirl with pink headphone and blue hair, occlusion shadow, specular reflection, rim light, unreal engine, octane render, artgerm, artstation, art by hiroaki samura and jiro matsumoto and yusuke murata, high quality, intricate detailed 8 k, fantasy illustration, extremely beautiful and aesthetic shape of body

highly detailed color portrait of Artemis, the goddess of wild animals, beautiful face, intricate details, cinematic, Hasselblad Medium Format Film Camera, fully covered in ancient tattoos, hyper-realistic, mystical energy in the air, heroic fantasy art, centered, symmetrical, detailed eyes, special effects, diffused light, volumetric lighting, hd octane render, 4K, in the style of todd mcfarlane

portrait of a gorgeous white balinese smiling woman, detailed eyes, she is wearing a white balinese kebaya, high resolution, 8k, proportional, ultra detailed, black and white photography, play of lights, realistic undistracted facial features Negative: disproportionate,

professional portrait photograph, of a gorgeous Queen Of Dragons with short wavy silver hair, wearing jewelry garments, ((sultry flirty look)), a beautiful symmetrical face, gothic makeup, ((standing outside in snowy mountain)), stunning garden upscale environment, ultra realistic, concept art, elegant, highly detailed, intricate, sharp focus, depth of field, f/1.8, 85mm, medium shot, mid shot, (centered image composition), (professionally color graded), ((bright soft diffused light)), volumetric fog, trending on instagram, trending on tumblr, hdr 4k, 8k

Harley Quinn blue hair, occlusion shadow, specular reflection, rim light, unreal engine, octane render, artgerm, artstation, art by hiroaki samura and jiro matsumoto and yusuke murata, high quality, intricate detailed 8 k, fantasy illustration, extremely beautiful and aesthetic shape of body

photograph close up portrait Harley Quinn, long hair, smiling, stoic cinematic 4k epic detailed 4k epic detailed photograph shot on kodak detailed bokeh cinematic hbo teal moody

some prompts to generate images:

1. A peaceful mountain landscape with a river flowing through it
2. An epic space battle between alien ships in orbit around a planet
3. A magical forest with glowing mushrooms and fairies flying around
4. A futuristic cityscape with flying cars and towering skyscrapers
5. A majestic dragon flying over a medieval castle
6. A serene beach scene with palm trees and crystal-clear water
7. A post-apocalyptic wasteland with a lone survivor trekking through it
8. A steampunk city with clockwork machines and airships
9. A creepy haunted house with ghosts and paranormal activity
10. A majestic unicorn standing on a mountaintop with a rainbow in the background

some elegant prompts for generating images:

1. A tranquil forest glade with a small stream flowing through it, surrounded by tall trees and colorful wildflowers. The image should be detailed and high resolution, with a warm and inviting atmosphere.

2. A majestic eagle soaring over a snow-capped mountain range at sunset. The image should be stylized and rendered in a painterly style, with rich colors and dramatic lighting.

3. A futuristic cityscape at night, with neon lights and holographic billboards filling the skyline. The image should be highly detailed and rendered in a photorealistic style, with dynamic camera angles and vivid colors.

4. A magical garden filled with exotic plants and animals, with a mystical castle in the distance. The image should be detailed and colorful, with an otherworldly atmosphere and a sense of wonder.

5. A stormy seascape with a lighthouse standing tall against the crashing waves. The image should be rendered in a realistic style, with dramatic lighting and textures that convey the power of the ocean.

6. A space station orbiting a distant planet, with sleek ships flying in and out of its docking bays. The image should be highly detailed and rendered in a futuristic style, with a sense of scale and grandeur.

7. A medieval village nestled in the rolling hills of the countryside, with a castle towering above it. The image should be rendered in a painterly style, with warm colors and soft lighting that evoke a sense of nostalgia.

8. A fantastical underwater world filled with colorful coral reefs, schools of fish, and mermaids swimming through the crystal-clear water. The image should be highly detailed and rendered in a stylized, almost dreamlike style.

9. A bustling city street at night, with a busy intersection and colorful lights filling the scene. The image should be highly detailed and rendered in a photorealistic style, with dynamic camera angles and a sense of energy and movement.

10. A tranquil garden with a small pond, surrounded by trees and flowers in full bloom. The image should be rendered in a soft, painterly style, with warm colors and gentle lighting that convey a sense of peace and tranquility.

Characteristics of Good Prompts:

Good prompts for AI to analyze images should be specific, relevant, and clear. Specific prompts provide detailed information about the image being analyzed, including features such as color, texture, and shape. Relevant prompts provide information that is relevant to the task being performed by the AI system. Clear prompts are easy for the AI to understand and interpret accurately.

Challenges and Potential Solutions:

Creating effective prompts for AI to analyze images can be challenging due to factors such as variability in image content and context, ambiguity in natural language prompts, and difficulty in creating accurate visual prompts. To address these challenges, potential solutions include developing better natural language processing algorithms, using pre-existing visual data to create more accurate prompts, and leveraging crowdsourcing to collect more accurate and diverse data.

public multinational companies that use AI to analyze images:

1. Google LLC - Google uses AI to analyze images for its image search, Google Lens, and other products.

2. Facebook, Inc. - Facebook uses AI to analyze images for facial recognition, object recognition, and content moderation.

3. Amazon.com, Inc. - Amazon uses AI to analyze images for its product recommendations, image search, and other services.

4. Microsoft Corporation - Microsoft uses AI to analyze images for its Azure Cognitive Services, Bing Image Search, and other products.

5. IBM Corporation - IBM uses AI to analyze images for its Watson Visual Recognition and other products.

6. NVIDIA Corporation - NVIDIA uses AI to analyze images for its GeForce Experience and other products.

7. Tesla, Inc. - Tesla uses AI to analyze images for its Autopilot system, which enables its vehicles to detect and respond to their surroundings.

8. Apple Inc. - Apple uses AI to analyze images for its Photos app, which includes features such as object recognition and facial recognition.

9. Adobe Inc. - Adobe uses AI to analyze images for its Creative Cloud suite of products, including Photoshop and Lightroom.

10. Intel Corporation - Intel uses AI to analyze images for its RealSense depth cameras, which can capture and analyze 3D images in real time.

quadrant analysis of AI for image analysis:

Quadrant 1: Image Classification

Image classification is the process of assigning labels to images based on their content. This quadrant includes AI techniques such as Convolutional Neural Networks (CNNs), which can be trained on large datasets of labeled images to accurately classify new images. Image classification has many practical applications, including object recognition, facial recognition, and medical image analysis.

Quadrant 2: Object Detection

Object detection is the process of identifying and localizing objects within an image. This quadrant includes AI techniques such as Region-based CNNs (R-CNNs) and Single Shot Detectors (SSDs), which can detect multiple objects within an image and provide information about their location and size. Object detection has applications in areas such as self-driving cars, surveillance, and robotics.

Quadrant 3: Image Segmentation

Image segmentation is the process of dividing an image into multiple regions or segments based on the content of the image. This quadrant includes AI techniques such as Fully Convolutional Networks (FCNs) and U-Net, which can separate an image into distinct regions that can be analyzed separately. Image segmentation has applications in medical image analysis, satellite image analysis, and computer vision.

Quadrant 4: Image Generation

Image generation is the process of creating new images from scratch, based on a set of rules or parameters. This quadrant includes AI techniques such as Generative Adversarial Networks (GANs), which can create new images that look like they were created by humans. Image generation has applications in areas such as art, fashion, and video game design.

Overall, AI for image analysis has a wide range of applications and continues to advance rapidly with the development of new techniques and algorithms.

Conclusion:

Creating good prompts for AI to analyze images is crucial for accurate image analysis and interpretation. By understanding the different types of image prompts, the characteristics of good prompts, and the challenges associated with creating effective prompts, we can develop better AI systems that can accurately analyze visual data.

the prominent companies in the field of AI for image analysis, along with some of their notable leaders:

1. Google - Sundar Pichai (CEO of Google)
2. Microsoft - Satya Nadella (CEO of Microsoft)
3. Amazon - Jeff Bezos (Founder and former CEO of Amazon)
4. Facebook - Mark Zuckerberg (CEO of Facebook)
5. NVIDIA - Jensen Huang (Founder and CEO of NVIDIA)
6. IBM - Arvind Krishna (CEO of IBM)
7. Intel - Pat Gelsinger (CEO of Intel)
8. Apple - Tim Cook (CEO of Apple)

These leaders may not be directly involved in the day-to-day operations of their companies' AI image analysis efforts, but they are likely to be involved in setting the overall strategy and direction of the organization.

References:

1. Krizhevsky, A., Sutskever, I., & Hinton, G. E. (2012). ImageNet classification with deep convolutional neural networks. In Advances in neural information processing systems (pp. 1097-1105).
2. Wang, L., Tao, D., & Gao, X. (2018). Deep learning for visual understanding: A review. Neurocomputing, 300, 53-71.
3. Socher, R., Huval, B., Bath, B., Manning, C. D., & Ng, A. (2014). Convolutional-recursive deep learning for 3D object classification. In Advances in neural information processing systems (pp. 656-664).
4. Deng, J., Dong, W., Socher, R., Li, L. J., Li, K., & Fei-Fei, L. (2009). ImageNet: A large-scale hierarchical image database. In 2009 IEEE conference on computer vision and pattern recognition (pp. 248-255). IEEE.