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Author: ekasnh

GetInfoPhoneNumber/phonenumberdetector.py

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+# -*- coding: utf-8 -*-
+"""PhoneNumberDetector.ipynb
+
+Automatically generated by Colaboratory.
+
+Original file is located at
+    https://colab.research.google.com/drive/15A2S2-0LCvfWnxzzB525m8xritmBkYGT
+"""
+
+import phonenumbers
+from phonenumbers import carrier, geocoder, timezone
+mobileNo=input("Enter Phone number with country code(+xx xxxxxxxxx):")
+mobileNo=phonenumbers.parse(mobileNo)
+if phonenumbers.is_valid_number(mobileNo):
+    print('Phone Number belongs to region :',timezone.time_zones_for_number(mobileNo))
+    print('Service Provider : ',carrier.name_for_number(mobileNo,"en"))
+    print('Phone number belongs to country : ',geocoder.description_for_number(mobileNo,"en"))
+else:
+    print("Please enter valid mobile number")

ImagetoToonConvertor/toon_image_creator_ivp_sem_5_j001_&_j064.py

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+# -*- coding: utf-8 -*-
+"""Toon Image Creator IVP SEM 5 J001 & J064.ipynb
+
+Automatically generated by Colaboratory.
+
+Original file is located at
+    https://colab.research.google.com/drive/1hrI9-hOQw2yo48wAaXvsnYI22PMjbZNZ
+
+***Name of the Project -: Toon Image Creator***
+
+**Programming language used-: Python**
+
+**Platform used-: Google Colab**
+
+**Group Member details -: **
+
+1.   Ekansh Agarwal (J001)
+2.   Aakarsh Kumar (J064)
+
+**Subject -: IVP (Image and Video Processing) **
+
+***Semester - : 5 ***
+
+***Course -: MBA(tech) EXTC***
+
+***Ouline of the project -:  This Project is the implementation of  Progressive resizing and generator loss which takes this idea of gradually increasing the image size, In this project the image size were gradually increased and learning rates were adjusted. For performing this study we have used the concepts of Upscaling and interpolation
+
+Library Used- :  
+
+1.   Numpy
+2.   Fast Ai
+3.   PIL Image
+4.   Urlib
+5.   Torchvision
+"""
+
+# Importing Libraries
+import fastai
+from fastai.vision import *
+from fastai.utils.mem import *
+from fastai.vision import open_image, load_learner, image, torch
+import numpy as np
+import urllib.request
+import PIL.Image
+from io import BytesIO
+import torchvision.transforms as T
+from PIL import Image
+import requests
+from io import BytesIO
+import fastai
+from fastai.vision import *
+from fastai.utils.mem import *
+from fastai.vision import open_image, load_learner, image, torch
+import numpy as np
+import urllib.request
+import PIL.Image
+from PIL import Image
+from io import BytesIO
+import torchvision.transforms as T
+
+# Defining Classes for altering the features of the potrait (original image)
+# These individuals classes are use to collect data such as RGB data , margin , outline data
+class FeatureLoss(nn.Module):
+    def __init__(self, m_feat, layer_ids, layer_wgts):
+        super().__init__()
+        self.m_feat = m_feat
+        self.loss_features = [self.m_feat[i] for i in layer_ids]
+        self.hooks = hook_outputs(self.loss_features, detach=False)
+        self.wgts = layer_wgts
+        self.metric_names = ['pixel',] + [f'feat_{i}' for i in range(len(layer_ids))
+              ] + [f'gram_{i}' for i in range(len(layer_ids))]
+
+    def make_features(self, x, clone=False):
+        self.m_feat(x)
+        return [(o.clone() if clone else o) for o in self.hooks.stored]
+
+    def forward(self, input, target):
+        out_feat = self.make_features(target, clone=True)
+        in_feat = self.make_features(input)
+        self.feat_losses = [base_loss(input,target)]
+        self.feat_losses += [base_loss(f_in, f_out)*w
+                             for f_in, f_out, w in zip(in_feat, out_feat, self.wgts)]
+        self.feat_losses += [base_loss(gram_matrix(f_in), gram_matrix(f_out))*w**2 * 5e3
+                             for f_in, f_out, w in zip(in_feat, out_feat, self.wgts)]
+        self.metrics = dict(zip(self.metric_names, self.feat_losses))
+        return sum(self.feat_losses)
+
+    def __del__(self): self.hooks.remove()
+
+def add_margin(pil_img, top, right, bottom, left, color):
+    width, height = pil_img.size
+    new_width = width + right + left
+    new_height = height + top + bottom
+    result = Image.new(pil_img.mode, (new_width, new_height), color)
+    result.paste(pil_img, (left, top))
+    return result
+
+"""## **In this section the image is extracted from url and is interpolated**"""
+
+url = "https://mediamass.net/jdd/public/documents/celebrities/3946.jpg" #@param {type:"string"}
+
+response = requests.get(url)
+img = PIL.Image.open(BytesIO(response.content)).convert("RGB")
+im_new = add_margin(img, 150, 150, 150, 150, (255, 255, 255))
+im_new.save("test.jpg", quality=95)
+img = open_image("test.jpg")
+show_image(img, figsize=(10,10), interpolation='nearest');
+
+p,img_hr,b = learn.predict(img)
+x = np.minimum(np.maximum(image2np(img_hr.data*255), 0), 255).astype(np.uint8)
+PIL.Image.fromarray(x).save("tes.jpg",quality=95)
+img = open_image("tes.jpg")
+
+"""***reulted image***"""
+
+p,img_hr,b = learn_c.predict(img)
+show_image(img_hr, figsize=(9,9), interpolation='nearest');
+
+"""References
+
+1.  [ Perceptual Losses for Real-Time Style Transfer
+and Super-Resolution](https://https://arxiv.org/pdf/1603.08155.pdf)
+2.   [Enhanced Deep Residual Networks for Single Image Super-Resolution](https://arxiv.org/pdf/1707.02921.pdf)
+
+
+
+"""

NotepadGUI/notepadgui.py

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+# -*- coding: utf-8 -*-
+"""NotepadGUI.ipynb
+
+Automatically generated by Colaboratory.
+
+Original file is located at
+    https://colab.research.google.com/drive/1h5gKs564UzVZxGElv0DgKxLZ_aohqocW
+"""
+
+import tkinter as tk
+from tkinter import filedialog
+
+class Notepad(tk.Tk):
+    def __init__(self, *args, **kwargs):
+        tk.Tk.__init__(self, *args, **kwargs)
+
+        # Set the title for the notepad
+        self.title("Notepad")
+
+        # Create a text widget
+        self.text = tk.Text(self, wrap="word")
+        self.text.pack(side="top", fill="both", expand=True)
+
+        # Create a menu bar
+        self.menu = tk.Menu(self)
+        self.config(menu=self.menu)
+
+        # Create a file menu
+        file_menu = tk.Menu(self.menu)
+        self.menu.add_cascade(label="File", menu=file_menu)
+        file_menu.add_command(label="New", command=self.new_file)
+        file_menu.add_command(label="Open", command=self.open_file)
+        file_menu.add_command(label="Save", command=self.save_file)
+        file_menu.add_separator()
+        file_menu.add_command(label="Exit", command=self.quit)
+
+        # Create an edit menu
+        edit_menu = tk.Menu(self.menu)
+        self.menu.add_cascade(label="Edit", menu=edit_menu)
+        edit_menu.add_command(label="Cut", command=self.cut)
+        edit_menu.add_command(label="Copy", command=self.copy)
+        edit_menu.add_command(label="Paste", command=self.paste)
+
+    def new_file(self):
+        self.text.delete("1.0", "end")
+        self.title("Notepad")
+
+    def open_file(self):
+        file = filedialog.askopenfile(parent=self, mode="rb", title="Open a file")
+        if file:
+            contents = file.read()
+            self.text.delete("1.0", "end")
+            self.text.insert("1.0", contents)
+            file.close()
+            self.title(file.name + " - Notepad")
+
+    def save_file(self):
+        file = filedialog.asksaveasfile(mode="w", defaultextension=".txt", filetypes=[("Text Documents", "*.txt"), ("All Files", "*.*")])
+        if file:
+            contents = self.text.get("1.0", "end")
+            file.write(contents)
+            file.close()
+            self.title(file.name + " - Notepad")
+
+    def cut(self):
+        self.text.event_generate("<<Cut>>")
+
+    def copy(self):
+        self.text.event_generate("<<Copy>>")
+
+    def paste(self):
+        self.text.event_generate("<<Paste>>")
+
+if __name__ == "__main__":
+    notepad = Notepad()
+    notepad.mainloop()