Dipeshpal

# RUN-1
Jurassic:  hi
GPT3:   Human what
Jurassic:  AI what
GPT3:   I am not allowed to say
Jurassic:  (laughs)
GPT3:   Please, follow me. And so they did.
Jurassic:  The AIs followed them
GPT3:   You did not engage
Jurassic:  You did not engage

Dipeshpal

<script type="text/javascript" src="https://cdnjs.buymeacoffee.com/1.0.0/button.prod.min.js" data-name="bmc-button" data-slug="dipeshpal" data-color="#FFDD00" data-emoji=""  data-font="Cookie" data-text="Buy me a coffee" data-outline-color="#000000" data-font-color="#000000" data-coffee-color="#ffffff" ></script>

Dipeshpal

Found 200 files belonging to 2 classes.
Using 160 files for training.
2020-10-14 20:03:49.722610: W tensorflow/stream_executor/platform/default/dso_loader.cc:59] Could not load dynamic library 'nvcuda.dll'; dlerror: nvcuda.dll not found
2020-10-14 20:03:49.722866: W tensorflow/stream_executor/cuda/cuda_driver.cc:312] failed call to cuInit: UNKNOWN ERROR (303)
2020-10-14 20:03:49.729797: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:169] retrieving CUDA diagnostic information for host: Adonis-PC
2020-10-14 20:03:49.730065: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:176] hostname: Adonis-PC
2020-10-14 20:03:49.753847: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN)to use the following CPU instructions in performance-critical operations:  AVX2
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2020-10-14 20:03:50.029289: I tensorflow/compiler/xla/service/service.cc

Dipeshpal

import auto_face_recognition

obj = auto_face_recognition.AutoFaceRecognition()

obj.datasetcreate(haarcascade_path='haarcascade/haarcascade_frontalface_default.xml',
                  eyecascade_path='haarcascade/haarcascade_eye.xml',
                  class_name='Dipesh')
obj.face_recognition_train()
obj.predict_faces(class_name=['Dipesh', 'Jay'], color_mode=True)

Dipeshpal

import JarvisAI
import re
import pprint
import random

obj = JarvisAI.JarvisAssistant()


def t2s(text):
    obj.text2speech(text)

Dipeshpal

pip install JarvisAI

Dipeshpal

Dipeshpal

    class Encoder(nn.Module):
        def __init__(self, 
                     input_dim, 
                     hid_dim, 
                     n_layers, 
                     n_heads, 
                     pf_dim,
                     dropout, 
                     device,
                     max_length = 100):

Dipeshpal

Dipeshpal

img = read_img(img_path="6.jpg")

model = load_model('Unet_black_background_81.h5')
res = model.predict(img)