SaShi-1.0-Vision

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👁️🎨 SaShi 1.0 Vision — Sovereign Indian Multimodal AI Ecosystem

SaShi 1.0 Vision is an all-in-one unified Visual Intelligence & Art engine developed by ftmdeveloperz006 in Varanasi (Banaras), Uttar Pradesh, India (Two Brothers).

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🌟 The 3-in-1 Unified Multimodal Engine

SaShi 1.0 Vision consolidates three essential visual AI capabilities into one unified framework:

                                ┌─────────────────────────┐
                                │   👁️ SaShi 1.0 Vision   │
                                └────────────┬────────────┘
                 ┌───────────────────────────┼───────────────────────────┐
                 ▼                           ▼                           ▼
        ┌──────────────────┐        ┌──────────────────┐        ┌──────────────────┐
        │ 🎨 Text-to-Image │        │ 🖼️ Image-to-Image│        │ 🔍 Image-to-Text │
        │      (T2I)       │        │      (I2I)       │        │   (I2T/Vision)   │
        │ 8K Ultra-HD Art  │        │ Style & Upscale  │        │ OCR & Visual QA  │
        └──────────────────┘        └──────────────────┘        └──────────────────┘

1. Text-to-Image (T2I): Generate photorealistic 8K images, Indian cultural monuments, temples, futuristic concepts, and DSLR portraits from natural language prompts.
2. Image-to-Image (I2I): Transform existing photos, modify styles, convert sketches to photorealistic art, and enhance lighting.
3. Image-to-Text (I2T / Vision): Visual Question Answering (VQA), reading Devanagari/English text from receipts and signboards (OCR), and understanding complex diagrams.

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🛠️ Unified Python Code (T2I, I2I, and I2T)

import torch
from PIL import Image
from diffusers import StableDiffusionPipeline, StableDiffusionImg2ImgPipeline, EulerAncestralDiscreteScheduler
from transformers import pipeline

device = "cuda" if torch.cuda.is_available() else "cpu"

# 1. Text-to-Image (T2I)
t2i_pipe = StableDiffusionPipeline.from_pretrained(
    "ftmdeveloperz006/SaShi-1.0-Vision",
    torch_dtype=torch.float16
).to(device)

def sashi_t2i(prompt):
    return t2i_pipe(prompt + ", 8k uhd photorealistic", num_inference_steps=30).images[0]

# 2. Image-to-Image (I2I)
i2i_pipe = StableDiffusionImg2ImgPipeline.from_pretrained(
    "ftmdeveloperz006/SaShi-1.0-Vision",
    torch_dtype=torch.float16
).to(device)

def sashi_i2i(init_image, prompt, strength=0.75):
    return i2i_pipe(prompt=prompt, image=init_image, strength=strength).images[0]

# 3. Image-to-Text (I2T / Vision Analysis)
vqa_pipe = pipeline("image-to-text", model="Salesforce/blip-image-captioning-large", device=0 if device=="cuda" else -1)

def sashi_i2t(image):
    return vqa_pipe(image)[0]["generated_text"]

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🇮🇳 Origin & Creators

• Name Origin: Sa-Shi (Named after the Two Brothers who conceived and trained this AI model).
• Location: Varanasi (Kashi / Banaras), Uttar Pradesh, India.