Machine Made Max - BlitzCoder.net

-=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- (c) WidthPadding Industries 1987 0\|644\|0 -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=-
Socoder -> AI Threads -> Machine Made Max
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Sun, 19 Mar 2023, 07:41
Jayenkai	Aww, you mean the video above wasn't "real"?! -=-=- ''Load, Next List!''
Sun, 19 Mar 2023, 07:58
spinal	Oh, that was real, but its just a static image with a 5 frame mouth. I want to move the head around. -=-=- Check out my excellent homepage!
Sun, 19 Mar 2023, 08:05
Jayenkai	Oh, ok.
Sun, 19 Mar 2023, 09:54
spinal	OK, I did not expect this to work as well as it is doing... Stole, edited and traced some face parts from https://avatarmaker.net/create-avatar No idea how I'm going to manage to do the hair though, I guess it will take multiple layers. -=-=- Check out my excellent homepage!
Sun, 19 Mar 2023, 10:11
Jayenkai	Yikes!!! That's awesome!
Sun, 19 Mar 2023, 14:11
spinal	View on YouTube Anyone got any better ideas for an idle animation? -=-=- Check out my excellent homepage!
Sun, 19 Mar 2023, 15:45
Jayenkai	Could he occasionally glitchily tilt his head to the side? -=-=- ''Load, Next List!''
Sun, 19 Mar 2023, 16:15
spinal	Yes, but if he's talking the frame rate drops so low that his mouth stops moving ðŸ˜… -=-=- Check out my excellent homepage!
Sun, 19 Mar 2023, 16:53
Jayenkai	Dang. ... Because it's drawing the face, or because it's drawing at all? If you added a constantly moving background of Max-style stripes, can you keep those going at full speed whilst, in the background, drawing the face to a buffer and popping it on top? Eg, the face could be a constant 15fps and the backdrop 60. It "probably" won't be as noticeable. You'd need two face-buffers. One currently being drawn, the other displayed on the screen top of the lines. -=-=- ''Load, Next List!''
Mon, 20 Mar 2023, 04:01
spinal	Currently, the eyes (ouline, pupils and whites), nose, ears, hair, face outline and mouth are all draw to a layer, then that layer is drawn to the screen. I did this so that I could rotate it as a single image rather than all the maths being done for every image. on the speaking side, as the audio data is being transfered to the output buffer thingy, I am setting the mouth size from the current byte being copied and the renderer is just reading whatever the current mouth size is when it updates. The renderer is currently not limited to any frame rate, it just goes as fast as it can. If I set it to say 60fps, then the mouth isnt updated fast enough. I just put an fps counter in, wothout limiting it does between 400 and 600 fps without adding the rotation. Adding the rotation drops is below 400 fps and the mounth does not animate fast enough. -=-=- Check out my excellent homepage!
Mon, 20 Mar 2023, 04:36
Jayenkai	Oh, so it's the rotation, then? Sounds like it's using basic 2D drawing methods. Aw well Blinking might help, though. And the eyebrows, too. Wiggle those features!! -=-=- ''Load, Next List!''
Mon, 20 Mar 2023, 04:47
spinal	View on YouTube
Mon, 20 Mar 2023, 04:52
Jayenkai	If MouthWide>0 then MouthWide=MouthWide-0.25 If audio>MouthWide then MouthWide=audio That way, the silence doesn't clamp the mouth shut. It should make for a more noticeable opening. -=-=- ''Load, Next List!''
Mon, 20 Mar 2023, 04:58
spinal	Currently its this... # Draw the mouth M1 = mouth if M1 > M: M = M1 # M/13107 frame = int(M/2500) M=M-32 if M<1024: M=1024 --v if frame == 0: buffer_image.blit(img_01, (mouth_x-(img_01.get_width()//2)+(space_xi),mouth_y+(space_yi))) if frame == 1: buffer_image.blit(img_02, (mouth_x-(img_02.get_width()//2)+(space_xi),mouth_y+(space_yi))) if frame == 2: buffer_image.blit(img_03, (mouth_x-(img_03.get_width()//2)+(space_xi),mouth_y+(space_yi))) if frame == 3: buffer_image.blit(img_04, (mouth_x-(img_04.get_width()//2)+(space_xi),mouth_y+(space_yi))) if frame == 4: buffer_image.blit(img_05, (mouth_x-(img_05.get_width()//2)+(space_xi),mouth_y+(space_yi))) if frame >= 5: buffer_image.blit(img_06, (mouth_x-(img_06.get_width()//2)+(space_xi),mouth_y+(space_yi))) --v mouth is a 16bit number from the audio buffer -=-=- Check out my excellent homepage!
Mon, 20 Mar 2023, 05:36
Jayenkai	Hmm.. Yeah, that does seem to be doing that. shrugs -=-=- ''Load, Next List!''
Mon, 20 Mar 2023, 05:56
Jayenkai	If "Mouth" is only the current millisecond's audio buffer value... that'll be why you're losing data between frames. Can you access the data from in between the frames? -=-=- ''Load, Next List!''
Mon, 20 Mar 2023, 07:31
spinal	I assume there's plenty of time to bung it in an array or something. Are you thinking maybe averaging the data over 500/fps frames or something? \|edit\| no wait, thats worse. [edit agian] Fixed... just moved the mouth sizing code to the buffer copy loop. -=-=- Check out my excellent homepage!
Mon, 20 Mar 2023, 12:21
spinal	Changed the mouth, fixed the animation speed (for the mouth). View on YouTube -=-=- Check out my excellent homepage!
Mon, 20 Mar 2023, 14:20
Jayenkai	Awesome! Could do with a more "jumps from looking one way to the other" behaviour when he glitches... could you do that, or have you not enough data to know when it's glitching? -=-=- ''Load, Next List!''
Mon, 20 Mar 2023, 16:09
spinal	In theory, yes, in practice.... This is a mess... def stutter_text(text): # Split the text into sentences sentences = re.split("(?<!\w\.\w.)(?<![A-Z][a-z]\.)(?<=\.\|\?)\s(?![0-9])", text) #print(text) # put a word after every text, to make the tts sound like it's continueing a sentence, then remove that word from the audio normal_audio_data, audio_rate, audio_format = speak(" test") test_size = int(len(normal_audio_data)) # Iterate over each sentence and stutter some of the words audio_data_list = [] glitch_list = [] for sentence in sentences: sentence = sentence + '.' print(sentence) # Split the sentence into words words = sentence.strip().split() # Check if there are any words in the sentence if len(words) == 0: continue # Process each word in the sentence i = 0 while i < len(words): # Choose a random number of words to speak normally num_normal_words = random.randint(5, 10) if i + num_normal_words > len(words): num_normal_words = len(words) - i # Speak the first few words normally normal_text = ' '.join(words[i:i+num_normal_words]) normal_text = normal_text + ' test ' # the word 'test' is removed from the audio afterwards. normal_audio_data, audio_rate, audio_format = speak(normal_text) normal_duration = len(normal_audio_data)-test_size audio_data_list.append(normal_audio_data[0:normal_duration]) # Check if there are any words left to stutter if i + num_normal_words >= len(words): break # Stutter the next word temp_audio_data, audio_rate, audio_format = speak(" test") test_size = int(len(temp_audio_data)) stuttered_word = words[i+num_normal_words] stuttered_word = stuttered_word + ' test ' stuttered_audio_data, audio_rate, audio_format = stutter(stuttered_word, test_size) # Get the duration of the word's audio stuttered_duration = (len(stuttered_audio_data)) / audio_rate # Repeat the stuttered word repeat_audio_data, audio_rate, audio_format = speak(stuttered_word) # Get the duration of the word's audio #duration = (len(normal_audio_data)-test_size) / audio_rate # Calculate the start and end times of the stuttered audio stuttered_start_time = 0 stuttered_end_time = stuttered_duration # Calculate the start and end frames of the stuttered audio stuttered_start_frame = int(stuttered_start_time * audio_rate) stuttered_end_frame = int(stuttered_end_time * audio_rate) # Concatenate the audio data and append it to the list audio_data_list.append(stuttered_audio_data[stuttered_start_frame:stuttered_end_frame]) # Get the duration of the word's audio repeat_duration = (len(repeat_audio_data)-test_size) / audio_rate # Calculate the start and end times of the stuttered audio repeat_start_time = 0 repeat_end_time = repeat_duration # Calculate the start and end frames of the stuttered audio repeat_start_frame = int(repeat_start_time * audio_rate) repeat_end_frame = int(repeat_end_time * audio_rate) audio_data_list.append(repeat_audio_data[repeat_start_frame:repeat_end_frame]) for p in range(int(repeat_duration)): glitch_list.append(0) # Move to the next word i += num_normal_words + 1 # Concatenate all the audio data and write it to a stream audio_data = np.concatenate(audio_data_list) global CHUNK global FORMAT global CHANNELS global RATE RATE = audio_rate global mouth global glitching player = pyaudio.PyAudio() stream = player.open(format=FORMAT, channels=CHANNELS, rate=RATE, input=True, frames_per_buffer=CHUNK, output=True) #stream.write(audio_data.tobytes()) for sample in audio_data: stream.write(sample.tobytes()) M1 = sample if M1 > mouth: mouth = M1 mouth = mouth - 4 if mouth < 1024: mouth = 1024 mouth = mouth - 4 if mouth < 1024: mouth = 1024 stream.stop_stream() stream.close() player.terminate() mouth = 1024 --v -=-=- Check out my excellent homepage!
Mon, 20 Mar 2023, 16:59
Jayenkai	Sure is I'm not going to argue, though. GotoJSE's lacking in error codes because by the time it's running, I've lost all knowledge of which parts of the original script are being processed at any given moment. -=-=- ''Load, Next List!''
Tue, 21 Mar 2023, 11:57
spinal	This code nearly detects the glitches, but weirdly not always. Thats a puzzle. ''' To install more voices (they WILL be needed) Open Regedit and navigate to Computer\HKEY_LOCAL_MACHINE\SOFTWARE\Microsoft\Speech_OneCore\ Right click 'Voices' and export the file. Open the file in Notepad++ or other text editor, then find+replace Speech_OneCore with Speech. Save the file, then double-click it to inport the keys back into the registry. This will import all of your installed voiced into the location that pyttsx3 is looking for. ''' import random import time import wave import tempfile import os os.environ['PYGAME_HIDE_SUPPORT_PROMPT'] = "hide" import numpy as np import pyttsx3 import pyaudio import re import sys import array from threading import Thread from datetime import datetime import math import openai from glitch_this import ImageGlitcher import wikipedia import requests import geocoder from geopy.geocoders import Nominatim def weather_data(query): return res.json(); def open_file(filepath): with open(filepath, 'r', encoding='utf-8') as infile: return infile.read() openai.api_key = open_file('PythonGPT3Tutorial-main/openaiapikey.txt') CHUNK = 1024 FORMAT = pyaudio.paInt16 CHANNELS = 1 RATE = 22050 random.seed(datetime.now().timestamp()) s_num = 0 is_voice_set = False mouth = 0 glitching = 0 old_glitch = 0 glitch_angle = 0 glitch_list = [] running = False M = 0 voice_num = 0 # Colours BACKGROUND = (255, 255, 255) def draw_stuff(): import pygame screen_width = 500 screen_height = 500 WINDOW = pygame.display.set_mode((screen_width, screen_height)) pygame.display.set_caption("Maximum Headspace") clock = pygame.time.Clock() global mouth, M, glitching, old_glitch, glitch_angle global running buffer_image = pygame.Surface((screen_width1.25, screen_height1.25), pygame.SRCALPHA) buffer_rect = buffer_image.get_rect() buffer_image.convert_alpha() # Define colors BLACK = (0, 0, 0) WHITE = (255, 255, 255) RED = (255, 0, 0) wallpaper_image = pygame.image.load('max/parts/wallpaper.png').convert() shoulders_image = pygame.image.load('max/parts/shoulders.png').convert_alpha() ears_image = pygame.image.load('max/parts/ears.png').convert_alpha() face_image = pygame.image.load('max/parts/face.png').convert_alpha() eyes_image = pygame.image.load('max/parts/eyes.png').convert_alpha() eyes1_image = pygame.image.load('max/parts/eye_whites.png').convert_alpha() eyes2_image = pygame.image.load('max/parts/eye_iris.png').convert_alpha() nose_image = pygame.image.load('max/parts/nose.png').convert_alpha() hair_image = pygame.image.load('max/parts/hair.png').convert_alpha() img_01 = pygame.image.load('max/parts/m1.png').convert_alpha() img_02 = pygame.image.load('max/parts/m2.png').convert_alpha() img_03 = pygame.image.load('max/parts/m3.png').convert_alpha() img_04 = pygame.image.load('max/parts/m4.png').convert_alpha() img_05 = pygame.image.load('max/parts/m5.png').convert_alpha() img_06 = pygame.image.load('max/parts/m6.png').convert_alpha() # Get the center and mouse positions center_x = screen_width / 2 center_y = (screen_height / 2) + 30 wallpaper_w, wallpaper_h = wallpaper_image.get_size() wallpaper_x = center_x - (wallpaper_w/2) wallpaper_y = center_y - (wallpaper_h/2) shoulders_w, shoulders_h = shoulders_image.get_size() shoulders_x = center_x - (shoulders_w/2) shoulders_y = screen_height - shoulders_h face_x = center_x - (face_image.get_width()/2) face_y = (center_y - (face_image.get_height()/2)) - 50 ears_x = center_x - (ears_image.get_width()/2) ears_y = center_y - (ears_image.get_height()/2) - 20 nose_x = center_x - (nose_image.get_width()/2) nose_y = center_y - (nose_image.get_height()/2) + 20 eyes_x = center_x - (eyes_image.get_width()/2) eyes_y = center_y - (eyes_image.get_height()/2) - 40 eyes1_x = center_x - (eyes1_image.get_width()/2) eyes1_y = eyes_y + 28 eyes2_x = center_x - (eyes2_image.get_width()/2) eyes2_y = eyes_y + 32 hair_x = face_x - 10 hair_y = face_y - 50 mouth_x = center_x mouth_y = center_y + 70 angle = 0 angle_direction = 0.005 # Set the initial position and velocity of the pixel x = 250 y = 250 vx = 2 vy = 2.5 pygame.font.init() font = pygame.font.SysFont("Arial", 18) wallpaper_angle = 0 glitcher = ImageGlitcher() gx = 0 gy = 0 gvx = 0 gvy = 0 while(running): pygame.event.pump() mouse_x, mouse_y = pygame.mouse.get_pos() # Update the position of the pixel x += vx y += vy # Bounce the pixel off the edges of the screen if x < 0 or x >= screen_width: vx = -vx if y < 0 or y >= screen_height: vy = -vy num_parts = 50 # how many face bits we want to move around # Calculate the spacing between the center and mouse circles space_x = (x - center_x) / (num_parts - 1) space_y = (y - center_y) / (num_parts - 1) #space_x = (mouse_x - center_x) / (num_parts - 1) #space_y = (mouse_y - center_y) / (num_parts - 1) ''' # Calculate the angle from the center of the window to the mouse pointer dx = abs(mouse_x - center_x) dy = center_y - mouse_y angle = math.atan2(dy, dx) * 180 / math.pi ''' buffer_image.fill((0, 0, 0, 0)) i=1 buffer_image.blit(ears_image, (ears_x+(space_xi),ears_y+(space_yi))) i=i+1 buffer_image.blit(face_image, (face_x+(space_xi),face_y+(space_yi))) i=i+2 buffer_image.blit(eyes1_image, (eyes1_x+(space_xi),eyes1_y+(space_yi))) # whites buffer_image.blit(eyes2_image, (eyes2_x+(space_x(i+2)),eyes2_y+(space_y(i+2)))) # pupils buffer_image.blit(eyes_image, (eyes_x+(space_xi),eyes_y+(space_yi))) # outline i=i-2 buffer_image.blit(hair_image, (hair_x+(space_xi),hair_y+(space_yi))) i=i+2.5 buffer_image.blit(nose_image, (nose_x+(space_xi),nose_y+(space_yi))) i=i-.5 # Draw the mouth frame = int(mouth/2500) if frame == 0: buffer_image.blit(img_01, (mouth_x-(img_01.get_width()//2)+(space_xi),mouth_y+(space_yi))) if frame == 1: buffer_image.blit(img_02, (mouth_x-(img_02.get_width()//2)+(space_xi),mouth_y+(space_yi))) if frame == 2: buffer_image.blit(img_03, (mouth_x-(img_03.get_width()//2)+(space_xi),mouth_y+(space_yi))) if frame == 3: buffer_image.blit(img_04, (mouth_x-(img_04.get_width()//2)+(space_xi),mouth_y+(space_yi))) if frame == 4: buffer_image.blit(img_05, (mouth_x-(img_05.get_width()//2)+(space_xi),mouth_y+(space_yi))) if frame >= 5: buffer_image.blit(img_06, (mouth_x-(img_06.get_width()//2)+(space_xi),mouth_y+(space_yi))) #WINDOW.fill(BACKGROUND) #WINDOW.blit(wallpaper_image, (wallpaper_x,wallpaper_y)) self = wallpaper_image.convert_alpha() rotate_image = pygame.transform.rotate(self, wallpaper_angle) rect = rotate_image.get_rect(center = buffer_rect.center) WINDOW.blit(rotate_image,rect) wallpaper_angle = (wallpaper_angle + 0.1) % 360 WINDOW.blit(shoulders_image, (shoulders_x,shoulders_y)) #old_angle = angle if glitching != old_glitch: if glitching == 1: angle = random.uniform(-10, 10) gx = x gy = y gvx = vx gvy = vy if glitching >1: angle = random.uniform(-10, 10) x = gx y = gy vx = gvx vy = gvy old_glitch = glitching #if M == 1024: self = buffer_image.convert_alpha() rotate_image = pygame.transform.rotate(self, angle) rect = rotate_image.get_rect(center = buffer_rect.center) WINDOW.blit(rotate_image,rect) #glitch_img = glitcher.glitch_image(rotate_image, 2, color_offset=False, gif=False) #WINDOW.blit(glitch_img, rect) #else: # WINDOW.blit(buffer_image, (0,0)) angle = angle + angle_direction if angle >= 3 or angle <= -3 : angle_direction = -angle_direction fps = str(int(clock.get_fps())) fps_text = font.render(fps, 1, pygame.Color("coral")) WINDOW.blit(fps_text, (10,0)) fps_text = font.render(str(frame), 1, pygame.Color("coral")) WINDOW.blit(fps_text, (10,20)) fps_text = font.render(str(glitching), 1, pygame.Color("coral")) WINDOW.blit(fps_text, (10,40)) # Update the display #pygame.display.update() pygame.display.flip() clock.tick(60) def gpt3_completion(prompt, engine='text-davinci-002', temp=0.7, top_p=1.0, tokens=400, freq_pen=0.0, pres_pen=0.0, stop=['<<END>>']): prompt = prompt.encode(encoding='ASCII',errors='ignore').decode() response = openai.Completion.create( engine=engine, prompt=prompt, temperature=temp, max_tokens=tokens, top_p=top_p, frequency_penalty=freq_pen, presence_penalty=pres_pen, stop=stop) text = response['choices'][0]['text'].strip() return text def speak(text): global is_voice_set global voice_num # Initialize the text-to-speech engine engine = pyttsx3.init('sapi5') # Set the text-to-speech parameters engine.setProperty('rate', 150) engine.setProperty('volume', 1.0) #engine.setProperty('pitch', random.uniform(0.9, 1.1)) # Set pitch to random value voices = engine.getProperty('voices') if is_voice_set == False: is_voice_set = True voice_num = 0 # Print all available voices print("Available voices:") for i, voice in enumerate(voices): print(f"Name: {voice.name}") if "mark - english" in voice.name.lower(): print(f"Mark is number {i}") voice_num = i ''' # Ask the user to select a voice print('') print('') voice_num = int(input("Select a voice: ")) if voice_num < 0 or voice_num >= len(voices): print("Invalid selection.") else: selected_voice = voices[voice_num] engine.setProperty('voice', selected_voice.id) else: engine.setProperty('voice', voices[voice_num].id) ''' engine.setProperty('voice', voices[voice_num].id) # Generate a temporary WAV file to save the audio data with tempfile.NamedTemporaryFile(delete=False) as f: file_path = f.name # Speak the text and save the audio data to the temporary WAV file engine.save_to_file(text, file_path) # Start the speech engine in a separate thread engine.startLoop(False) # Wait for the engine to finish speaking while engine.iterate(): time.sleep(0.1) # Print('Working...') # Stop the speech engine engine.stop() # Read the audio data from the temporary WAV file with wave.open(file_path, 'rb') as wav_file: audio_data = np.frombuffer(wav_file.readframes(-1), dtype=np.int16) audio_rate = wav_file.getframerate() audio_format = wav_file.getsampwidth() start_trim = 0 duration = len(audio_data)-1 end_trim = duration threshold = 10 while audio_data[start_trim] < threshold and start_trim < duration : start_trim = start_trim + 1 while audio_data[end_trim] < threshold and end_trim > 0 : end_trim = end_trim - 1 # Remove the temporary WAV file os.remove(file_path) return audio_data[start_trim:end_trim], audio_rate, audio_format def stutter(word, end_trim): global glitch_list # Speak the word and get the audio data, rate, and format audio_data, audio_rate, audio_format = speak(word) # Convert the audio data to a numpy array audio_data = np.frombuffer(audio_data, dtype=np.int16) # Choose a random position to stutter from #position = random.uniform(0.0, 0.5) # Get the duration of the word's audio duration = (len(audio_data)-end_trim) / audio_rate # Calculate the start and end times of the stuttered audio start_time = 0 end_time = duration * random.uniform(0.5, 0.7) if len(word) <= 10: # length of 3 + ' Test ' start_time = 0 end_time = duration # Calculate the start and end frames of the stuttered audio start_frame = int(start_time * audio_rate) end_frame = int(end_time * audio_rate) # Extract the stuttered audio and repeat it stuttered_audio = audio_data[start_frame:end_frame] #repeated_audio = np.concatenate([stuttered_audio] * 2) repeated_audio = array.array('h') stutter_type = random.randint(0, 1) spd = 100 num_times = random.randint(1, 3) # if num_times >1: # stutter_type = 0 for y in range(num_times): if stutter_type < 1: spd = spd + 8 sz = int(((len(stuttered_audio)-1)100)/spd) for x in range(sz): pos = int((xspd)/100) num = stuttered_audio[pos] repeated_audio.append(num) glitch_list.append(y) return repeated_audio, audio_rate, audio_format, y def stutter_text(text): # Split the text into sentences sentences = re.split("(?<!\w\.\w.)(?<![A-Z][a-z]\.)(?<=\.\|\?)\s(?![0-9])", text) #print(text) # put a word after every text, to make the tts sound like it's continueing a sentence, then remove that word from the audio normal_audio_data, audio_rate, audio_format = speak(" test") test_size = int(len(normal_audio_data)) # Iterate over each sentence and stutter some of the words audio_data_list = [] global glitch_list glitch_list = [] for sentence in sentences: sentence = sentence + '.' print(sentence) # Split the sentence into words words = sentence.strip().split() # Check if there are any words in the sentence if len(words) == 0: continue # Process each word in the sentence i = 0 number_of_times = 0 while i < len(words): ######################[ Normal speech first ]################################################### # Choose a random number of words to speak normally # num_normal_words = random.randint(2, 6) # if i + num_normal_words > len(words): # num_normal_words = len(words) - i # # Speak the first few words normally # normal_text = ' '.join(words[i:i+num_normal_words]) # normal_text = normal_text + ' test ' # the word 'test' is removed from the audio afterwards. # normal_audio_data, audio_rate, audio_format = speak(normal_text) # normal_duration = len(normal_audio_data)-test_size # audio_data_list.append(normal_audio_data[0:normal_duration]) # for c in range(normal_duration): glitch_list.append(0) # Check if there are any words left to stutter # if i + num_normal_words >= len(words): # break # ################################################################################################ ######################[ next stutter a word ]################################################### # Stutter the next word # temp_audio_data, audio_rate, audio_format = speak(" test") # test_size = int(len(temp_audio_data)) # stuttered_word = words[i+num_normal_words] # stuttered_word = stuttered_word + ' test ' # stuttered_audio_data, audio_rate, audio_format, number_of_times = stutter(stuttered_word, test_size) # # Get the duration of the word's audio # stuttered_duration = (len(stuttered_audio_data)) # # Calculate the start and end times of the stuttered audio # stuttered_start_time = 0 # stuttered_end_time = stuttered_duration # # Calculate the start and end frames of the stuttered audio # stuttered_start_frame = int(stuttered_start_time) # stuttered_end_frame = int(stuttered_end_time) # # Concatenate the audio data and append it to the list # audio_data_list.append(stuttered_audio_data[stuttered_start_frame:stuttered_end_frame]) # #for c in range(stuttered_duration): # glitch_list.append(1) # glitch_list is updated in teh stutter function ################################################################################################ ######################[ repeat the stutterd word ]############################################## # Repeat the stuttered word because it was not played in fullwhile stuttering. # repeat_audio_data, audio_rate, audio_format = speak(stuttered_word) # # Get the duration of the word's audio # repeat_duration = (len(repeat_audio_data)-test_size) # Calculate the start and end times of the stuttered audio # repeat_start_time = 0 # repeat_end_time = repeat_duration # # Calculate the start and end frames of the stuttered audio # repeat_start_frame = int(repeat_start_time) # repeat_end_frame = int(repeat_end_time) # audio_data_list.append(repeat_audio_data[repeat_start_frame:repeat_end_frame]) # for c in range(repeat_duration): glitch_list.append(number_of_times) ################################################################################################ # Move to the next word i += num_normal_words + 1 # Concatenate all the audio data and write it to a stream audio_data = np.concatenate(audio_data_list) global CHUNK global FORMAT global CHANNELS global RATE RATE = audio_rate global mouth global glitching player = pyaudio.PyAudio() stream = player.open(format=FORMAT, channels=CHANNELS, rate=RATE, input=True, frames_per_buffer=CHUNK, output=True) #stream.write(audio_data.tobytes()) sample_count = 0 for sample in audio_data: glitching = glitch_list[sample_count] sample_count = sample_count + 1 stream.write(sample.tobytes()) M1 = sample if M1 > mouth: mouth = M1 mouth = mouth - 4 if mouth < 1024: mouth = 1024 mouth = mouth - 4 if mouth < 1024: mouth = 1024 stream.stop_stream() stream.close() player.terminate() mouth = 1024 # Save the audio as a raw pcm file #global s_num #s_num += 1 #file_name = 'sentence_{}_{}.pcm'.format(s_num, audio_rate) #with open(file_name, 'ab') as f: # f.write(audio_data) def stutter_text_from_file(file_path): global running # Read the input text from the file with open(file_path, 'r') as f: text = f.read() # Split the text into sentences sentences = re.split("(?<!\w\.\w.)(?<![A-Z][a-z]\.)(?<=\.\|\?)\s(?![0-9])", text) # Process each sentence for i, sentence in enumerate(sentences): # Check if this is the last sentence and it doesn't end with punctuation if i == len(sentences) - 1 and sentence.strip() != '': # Add a period to the end of the sentence sentence = sentence.strip() + '.' # Check if the sentence is not empty if len(sentence.strip()) > 0: stutter_text(sentence.strip()) running = False print('Finished!') def stutter_text_from_ai(): global running while(1): prompt = input("Enter a question: ") responded = False #Lets check for specific looking commands if prompt=='exit': running=False os._exit(1) if 'time' in prompt: # Get the current time now = datetime.now() # Format the time as English time = now.strftime("%I:%M %p") # Print the time in English say_string = "The current time is " + time + ".." stutter_text(say_string) responded = True if 'date' in prompt: # Get the current time now = datetime.now() # Format the time as English date = now.strftime("%B %d, %Y") # Print the time in English say_string = "Today it is " + date + ".." stutter_text(say_string) responded = True if 'weather' in prompt: city='cramlington' query='q='+city; w_data=weather_data(query); #print_weather(w_data, city) stutter_text("{}'s temperature: {}Â°C ".format(city,w_data['main']['temp'])) stutter_text("Wind speed: {} m/s".format(w_data['wind']['speed'])) stutter_text("Description: {}".format(w_data['weather'][0]['description'])) stutter_text("Weather: {}".format(w_data['weather'][0]['main'])) #stutter_text(say_string) responded = True if responded == False: # if no specific commands asked, then make something up with openAI stutter_text('I think you want to know') stutter_text(prompt) text = gpt3_completion(prompt) # Split the text into sentences #sentences = re.split('[.?!\n]', text) sentences = re.split("(?<!\w\.\w.)(?<![A-Z][a-z]\.)(?<=\.\|\?)\s(?![0-9])", text) # Process each sentence for i, sentence in enumerate(sentences): # Check if this is the last sentence and it doesn't end with punctuation if i == len(sentences) - 1 and sentence.strip() != '': # Add a period to the end of the sentence sentence = sentence.strip() + '.' # Check if the sentence is not empty if len(sentence.strip()) > 0: stutter_text(sentence.strip()) if __name__ == '__main__': #result = wikipedia.search("Max Headroom", results = 5) #print(result) #print(result[1]) g = geocoder.ip('me') print(g.latlng) # Latitude & Longitude input Latitude = str(g.latlng[0]) Longitude = str(g.latlng[1]) # initialize Nominatim API geolocator = Nominatim(user_agent="geoapiExercises") location = geolocator.reverse(Latitude+","+Longitude) # Display print(location) #print(wikipedia.summary("Python Programming Language")) #with open('temp.txt', 'w') as f: # f.write(wikipedia.summary("Max Headroom", sentences = 5, auto_suggest = True)) file_path = "readme.txt" running=True # Stutter the text from the file t1 = Thread(target=stutter_text_from_file, args=(file_path,)) #t1 = Thread(target=stutter_text_from_ai) t1.start() t2 = Thread(target=draw_stuff) t2.start() t2.join() --v View on YouTube -=-=- Check out my excellent homepage!
Tue, 21 Mar 2023, 15:54
spinal	Adjusted the face layer, to be slightly larger than the window so that the hair doesn't get clipped. I think I've managed to detect the stuttering, just need a good looking way to express it visually. Also added blinking, this is done randomly. View on YouTube \|edit\| I just noticed, it looks a lot like Stephen Mulhern hosting Catchphrase... -=-=- Check out my excellent homepage!
Wed, 22 Mar 2023, 02:31
Jayenkai	\O/yeay\o/
Wed, 22 Mar 2023, 04:24
steve_ancell	@spinal That looks good mate.
Thu, 23 Mar 2023, 06:45
spinal	Here is the latest version, with a little better glitching... View on YouTube https://mastodon.social/@Spinal_Cord/110072659426350157 -=-=- Check out my excellent homepage!
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