Main readme

Python/main.py

@@ -42,7 +42,7 @@
 #Record a audio and get text
 with sr.Microphone() as source:
     print("Say something!")
-    audio = recognizer.listen(source, 3, 8)
+    audio = recognizer.listen(source, 3, 8) # 3: Number of seconds listening until something is detected, 8: Number of seconds listening
 
 audio_transcription = recognizer.recognize_google(audio)
 print(audio_transcription)
@@ -106,7 +106,6 @@ def move_and_rename(src_path, dest_folder):
     print("no model")
     #descriptive_text = openAI_call(audio_transcription)
 
-    # print(dall_e_prompt)
     response = openAI_client.images.generate(
         model="dall-e-3",
         prompt=complete_prompt,
@@ -136,14 +135,6 @@ def move_and_rename(src_path, dest_folder):
 
 
     def file_modification_stable(file_path, stability_duration=60, check_interval=40, timeout=3600):
-        """
-        Waits for a file's modification time to be stable for a given duration.
-        Args:
-            file_path: The path to the file to monitor.
-            stability_duration: The duration (in seconds) for which the file's modification time should be stable.
-            check_interval: How often (in seconds) to check the file's modification time.
-            timeout: The maximum time to wait in seconds.
-        """
         start_time = time.time()
         last_mod_time = None
         stable_start_time = None
@@ -168,11 +159,6 @@ def file_modification_stable(file_path, stability_duration=60, check_interval=40
             time.sleep(check_interval)
 
     def run_python_script(script_path):
-        """
-        Executes a Python script.
-        Args:
-            script_path: The path to the Python script to run.
-        """
         print(f"Running script {script_path}...")
         subprocess.run(["python", script_path], check=True)
 

README.md

@@ -3,7 +3,7 @@
 ###### ***Vania Bisbal - Jorge Muñoz***
 
 ----
-## *- About*
+## - About
 
 ### *What am I?*
 
@@ -17,16 +17,122 @@ Run the code and say what you want to conceptualize, I will project the result a
 
 The script automates the creation of a hologram from spoken words by transforming a voice description into a model or image, animating and rendering it in Blender, and then formatting video for a holographic display. The process involves speech-to-text, 3D modeling and animation, video editing, and hologram layout formatting, integrating different technologies to produce a holographic video from an initial spoken description.
 
-## *- Script*
+### *What will YOU need to make this work?*
+
+- **For the code:** 
+  - *Blender installed on your computer:* This code has been running on [Blender 4.0](https://www.blender.org/) for Mac on macOS Sonoma 14.4 
+  - OpenAI keys: To have acces to [OpenAI API](https://platform.openai.com/) and be able to use their models
+  - kittycad keys: To be able to generate AI 3D models using [ZOOCAD](https://zoo.dev/pricing) model
+- **For the artifact:** 
+  - Laser cut machine: To be able to cut the pieces of the structure
+  - 3 sheets (100x60) of 4mm plywood: For the base and the bottom of the structure
+  - 1 sheet (100x60) of 4mm methacrylate: For the columns and the pyramid
+  - Screen: The plans of the artifact are measured for a 30x26 cm screen. Be aware that as brighter the screen is a much better result you'll get. 
+
+## - Code
 
 ### *Main.py*
+
+This will be the main script that will control everything else. The script consists of three different parts. 
+
+- **Speech recognizer:** Will record the audio of the user asking for the desired object for inspiration, then will print the recorded audio to text and will assign it as the prompt.
+
+
+  ```python
+  recognizer = sr.Recognizer()
+  # Record a audio and get text
+  with sr.Microphone() as source:
+  	print("Say something!")
+  	audio = recognizer.listen(source, 3, 8) # 3: Number of seconds listening until something is detected, 8: Number of seconds listening
+
+  audio_transcription = recognizer.recognize_google(audio)
+  print(audio_transcription)
+  ```
+
+- **if model in text:** Once ```audio_transcription``` is defined, the script will look for the word ```model``` inside the transcription. If it's not inside, it will execute the first part of the condition, where we will use dall-e-3 to generate images as the user didn't ask for a model. 
+
+  ```python
+  Open_AI_prompt ="add a black background"
+
+  complete_prompt = audio_transcription + " and " + Open_AI_prompt
+  ```
+
+  Remember to use short prompts in ```Open_AI_prompt``` as the results will be significantly better. 
+
+  In this piece of code you will be able to modify the number of images, quality, proportion, prompt and the image generator for the images:
+
+  ```python
+      response = openAI_client.images.generate(
+          model="dall-e-3",
+          prompt=complete_prompt,
+          size="1024x1024",
+          quality="standard",
+          n=1,
+      )
+  ```
+
+  OpenAI will generate a url to see the image that the script will automatically download using ```requests``` library. 
+
+  After that, a static video of the image will be created using ```moviepy.editor```  where the duration can be specified ```video_duration = 20``` . Lastly, the script will wait for the video to be ready before opening ```Hologram_Video_Layout.py``` so it doesn't give the user an error. Using the following definition, the script will check if the file created with the ```moviepy.editor``` is still having changes in size (What will mean the process of creating it won't be fully done)
+
+  ```python
+      def file_modification_stable(file_path, stability_duration=60, check_interval=40, timeout=3600):
+          start_time = time.time()
+          last_mod_time = None
+          stable_start_time = None
+
+          while True:
+              if not os.path.exists(file_path):
+                  print(f"{file_path} does not exist yet.")
+                  last_mod_time = None  
+              else:
+                  current_mod_time = os.path.getmtime(file_path)
+                  if last_mod_time is None or current_mod_time != last_mod_time:
+                      last_mod_time = current_mod_time
+                      stable_start_time = time.time()  
+                  elif time.time() - stable_start_time >= stability_duration:
+                      print(f"File {file_path} has been stable for {stability_duration} seconds.")
+                      break
+
+              if time.time() - start_time > timeout:
+                  print("Timed out waiting for file to become stable.")
+                  break
+
+              time.sleep(check_interval)
+  ```
+
+  User will be able to determine the amount of time the script waits until checking, the time of stability and the time the definition will be running until stoping.
+
+  After this, when the file is stable, the script ```Hologram_Video_Layout.py``` will be opened.
+
+  ```python
+  def run_python_script(script_path):
+          print(f"Running script {script_path}...")
+          subprocess.run(["python", script_path], check=True)
+
+
+
+      file_path = '/Users/jorgemuyo/Desktop/Challenge/rendered_blender_video.mp4'
+      script_path = '/Users/jorgemuyo/Desktop/Challenge/Hologram_Video_Layout.py'
+      # Wait for the file to finish rendering and for the file modification time to be stable
+      file_modification_stable(file_path)
+
+      # Once the file is stable, run another script
+      run_python_script(script_path)
+  ```
+
+- **else:** This part of the script will be executed if the user says ```model``` in ```audio_transcription``` 
+
 ### *Blender_CAD.py*
+
+
+
 ### *Hologram_Video_Layout.py*
 ### *text_to_cad.py*
 ### *requirements.txt*
 
-## *- Artifact*
+## - Artifact
 
-## *- Final results*
+## - Final results
 
 ![](./IMG_MD/Captura_P.png)