Update app.py

app.py

@@ -21,7 +21,7 @@ import numpy as np
 
 MIN_WIDTH = 1920
 MIN_HEIGHT = 1080
-TARGET_ASPECT_RATIO = 16/9
+TARGET_ASPECT_RATIO = 16 / 9
 
 output_folder = "outputs"
 temp_dir = "temp_files"
@@ -30,74 +30,67 @@ os.makedirs(temp_dir, exist_ok=True)
 
 FOLDER_ID = "12S6adpanAXjf71pKKGRRPqpzbJa5XEh3"
 
+# Función para cargar proxies desde un archivo
 def load_proxies(proxy_file="proxys.txt"):
     try:
         with open(proxy_file, 'r') as f:
             proxies = [line.strip() for line in f if line.strip()]
         print(f"Loaded {len(proxies)} proxies from file")
-        return [requests_proxy.ProxyInfo(proxy=f"http://{proxy}") for proxy in proxies]
+        return [{"http": f"http://{proxy}", "https": f"http://{proxy}"} for proxy in proxies]
     except Exception as e:
         print(f"Error loading proxies: {e}")
         return []
 
+# Función para buscar imágenes en Google Custom Search API
 def search_google_images(query, num_images=1):
     try:
         api_key = os.getenv('GOOGLE_API_KEY')
         cse_id = os.getenv('GOOGLE_CSE_ID')
         proxies = load_proxies()
-        
+
         print(f"Buscando imágenes para: {query}")
-        
-        if not proxies:
-            print("No proxies available, trying without proxy")
-            with requests.Session() as session:
-                result = session.get(
-                    f"https://www.googleapis.com/customsearch/v1",
-                    params={
-                        "q": query,
-                        "cx": cse_id,
-                        "searchType": "image",
-                        "num": num_images * 3,
-                        "safe": 'off',
-                        "imgSize": 'LARGE',
-                        "imgType": 'imgTypeUndefined',
-                        "rights": 'cc_publicdomain|cc_attribute|cc_sharealike',
-                        "key": api_key
-                    }
-                ).json()
-        else:
-            with requests_proxy.ProxyManager(proxies) as proxy_manager:
-                result = proxy_manager.get(
-                    f"https://www.googleapis.com/customsearch/v1",
-                    params={
-                        "q": query,
-                        "cx": cse_id,
-                        "searchType": "image",
-                        "num": num_images * 3,
-                        "safe": 'off',
-                        "imgSize": 'LARGE',
-                        "imgType": 'imgTypeUndefined',
-                        "rights": 'cc_publicdomain|cc_attribute|cc_sharealike',
-                        "key": api_key
-                    }
-                ).json()
+
+        # Intenta con proxies si están disponibles
+        if proxies:
+            for proxy in proxies:
+                try:
+                    print(f"Trying with proxy: {proxy['http']}")
+                    result = requests.get(
+                        "https://www.googleapis.com/customsearch/v1",
+                        params={
+                            "q": query,
+                            "cx": cse_id,
+                            "searchType": "image",
+                            "num": num_images * 3,
+                            "safe": "off",
+                            "imgSize": "LARGE",
+                            "rights": "cc_publicdomain|cc_attribute|cc_sharealike",
+                            "key": api_key
+                        },
+                        proxies=proxy,
+                        timeout=10
+                    ).json()
+                    break  # Sale del bucle si la solicitud es exitosa
+                except Exception as e:
+                    print(f"Error using proxy {proxy['http']}: {e}")
+                    continue
         else:
-            with requests_proxy.ProxyManager(proxies) as proxy_manager:
-               result = proxy_manager.get(
-                   f"https://www.googleapis.com/customsearch/v1",
-                    params={
-                        "q": query,
-                        "cx": cse_id,
-                        "searchType": "image",
-                        "num": num_images * 3,
-                        "safe": 'off',
-                        "imgSize": 'HUGE',
-                        "imgType": 'photo',
-                        "rights": 'cc_publicdomain|cc_attribute|cc_sharealike',
-                        "key": api_key
-                    }
-                ).json()
-        
+            print("No proxies available, trying without proxy")
+            result = requests.get(
+                "https://www.googleapis.com/customsearch/v1",
+                params={
+                    "q": query,
+                    "cx": cse_id,
+                    "searchType": "image",
+                    "num": num_images * 3,
+                    "safe": "off",
+                    "imgSize": "LARGE",
+                    "rights": "cc_publicdomain|cc_attribute|cc_sharealike",
+                    "key": api_key
+                },
+                timeout=10
+            ).json()
+
         if 'items' in result:
             image_urls = []
             for item in result.get('items', []):
@@ -108,80 +101,81 @@ def search_google_images(query, num_images=1):
                         image_urls.append(item['link'])
                         if len(image_urls) >= num_images:
                             break
-            
+
             print(f"Encontradas {len(image_urls)} imágenes de tamaño adecuado")
             return image_urls
-        
+
         print("No se encontraron imágenes después de probar todos los proxies")
         return []
-            
+
     except Exception as e:
         print(f"Error general en la búsqueda de imágenes: {str(e)}")
         return []
 
-
+# Procesa una imagen para ajustar su tamaño
 def process_image(image):
     try:
         width, height = image.size
         current_ratio = width / height
-        
+
         if current_ratio > TARGET_ASPECT_RATIO:
             new_width = max(MIN_WIDTH, width)
             new_height = int(new_width / TARGET_ASPECT_RATIO)
         else:
             new_height = max(MIN_HEIGHT, height)
             new_width = int(new_height * TARGET_ASPECT_RATIO)
-        
+
         image = image.resize((new_width, new_height), Image.Resampling.LANCZOS)
         background = Image.new('RGB', (max(new_width, MIN_WIDTH), max(new_height, MIN_HEIGHT)), 'black')
-        
-        offset = ((background.width - image.width) // 2,
-                 (background.height - image.height) // 2)
+
+        offset = ((background.width - image.width) // 2, (background.height - image.height) // 2)
         background.paste(image, offset)
-        
+
         return background
     except Exception as e:
         print(f"Error processing image: {e}")
         return None
 
+# Descarga una imagen desde una URL
 def download_image(url):
     proxies = load_proxies()
     if not proxies:
         proxies = [None]
-    
+
     for proxy in proxies:
         try:
             response = requests.get(url, proxies=proxy, timeout=10)
             image = Image.open(BytesIO(response.content))
-            
+
             if image.mode in ('RGBA', 'LA') or (image.mode == 'P' and 'transparency' in image.info):
                 background = Image.new('RGB', image.size, (0, 0, 0))
                 background.paste(image, mask=image.split()[-1])
                 image = background
-            
+
             processed_image = process_image(image)
             if processed_image:
                 return processed_image
-            
         except Exception as e:
             print(f"Error downloading image with proxy {proxy}: {e}")
             continue
     return None
 
+# Crea un clip animado a partir de una imagen
 def create_animated_clip(image, duration=5, zoom_factor=1.1):
     img_array = np.array(image)
     img_clip = ImageClip(img_array).set_duration(duration)
-    
+
     if img_clip.size[0] < MIN_WIDTH or img_clip.size[1] < MIN_HEIGHT:
         img_clip = img_clip.resize(width=MIN_WIDTH, height=MIN_HEIGHT)
-    
+
     return img_clip.resize(lambda t: 1 + (zoom_factor - 1) * t / duration)
 
+# Concatena clips de video basados en palabras clave
 def concatenate_google_images(keywords, clip_duration=5, num_images_per_keyword=1):
     keyword_list = [keyword.strip() for keyword in keywords.split(",") if keyword.strip()]
     if not keyword_list:
         keyword_list = ["nature"]
-    
+
     video_clips = []
     for keyword in keyword_list:
         try:
@@ -196,13 +190,14 @@ def concatenate_google_images(keywords, clip_duration=5, num_images_per_keyword=
         except Exception as e:
             print(f"Error processing keyword '{keyword}': {e}")
             continue
-    
+
     if not video_clips:
         return ColorClip(size=(MIN_WIDTH, MIN_HEIGHT), color=[0, 0, 0], duration=5)
-    
+
     random.shuffle(video_clips)
     return concatenate_videoclips(video_clips, method="compose")
 
+# Ajusta la música de fondo para que coincida con la duración del video
 def adjust_background_music(video_duration, music_file):
     try:
         music = AudioFileClip(music_file)
@@ -216,30 +211,31 @@ def adjust_background_music(video_duration, music_file):
         print(f"Error adjusting music: {e}")
         return None
 
+# Combina audio y video en un solo archivo
 def combine_audio_video(audio_file, video_clip, music_clip=None):
     try:
         audio_clip = AudioFileClip(audio_file)
         total_duration = audio_clip.duration + 2
-        
+
         video_clip = video_clip.loop(duration=total_duration)
         video_clip = video_clip.set_duration(total_duration).fadeout(2)
-        
+
         final_clip = video_clip.set_audio(audio_clip)
         if music_clip:
             music_clip = music_clip.set_duration(total_duration).audio_fadeout(2)
             final_clip = final_clip.set_audio(CompositeAudioClip([audio_clip, music_clip]))
-        
+
         output_filename = f"final_video_{int(time.time())}.mp4"
         output_path = os.path.join(output_folder, output_filename)
-        
+
         final_clip.write_videofile(output_path, codec="libx264", audio_codec="aac", fps=24)
-        
+
         final_clip.close()
         video_clip.close()
         audio_clip.close()
         if music_clip:
             music_clip.close()
-            
+
         return output_path
     except Exception as e:
         print(f"Error combining audio and video: {e}")
@@ -247,6 +243,7 @@ def combine_audio_video(audio_file, video_clip, music_clip=None):
             final_clip.close()
         return None
 
+# Sube un archivo al Google Drive
 def upload_to_google_drive(file_path, folder_id):
     try:
         creds = service_account.Credentials.from_service_account_info(
@@ -275,6 +272,17 @@ def upload_to_google_drive(file_path, folder_id):
         print(f"Error uploading to Google Drive: {e}")
         return None
 
+# Limpia archivos temporales
+def cleanup_temp_files():
+    try:
+        if os.path.exists(temp_dir) and os.path.isdir(temp_dir):
+            shutil.rmtree(temp_dir)
+            os.makedirs(temp_dir, exist_ok=True)
+        print("Temporal files cleaned up successfully.")
+    except Exception as e:
+        print(f"Error cleaning up temporary files: {e}")
+
+# Procesa la entrada del usuario y genera el video
 def process_input(text, txt_file, mp3_file, selected_voice, rate, pitch, keywords):
     try:
         if text.strip():
@@ -283,26 +291,25 @@ def process_input(text, txt_file, mp3_file, selected_voice, rate, pitch, keyword
             final_text = txt_file.decode("utf-8")
         else:
             raise ValueError("No text input provided")
-        
+
         audio_file = asyncio.run(text_to_speech(final_text, selected_voice, rate, pitch))
         if not audio_file:
             raise ValueError("Failed to generate audio")
-        
+
         video_clip = concatenate_google_images(keywords, clip_duration=5, num_images_per_keyword=1)
         if not video_clip:
             raise ValueError("Failed to generate video")
-        
+
         music_clip = None
         if mp3_file is not None:
             music_clip = adjust_background_music(video_clip.duration, mp3_file.name)
-        
+
         final_video_path = combine_audio_video(audio_file, video_clip, music_clip)
         if not final_video_path:
             raise ValueError("Failed to combine audio and video")
-        
+
         download_link = upload_to_google_drive(final_video_path, folder_id=FOLDER_ID)
         if download_link:
-            print(f"Video uploaded to Google Drive. Download link: {download_link}")
             return f"[Download video]({download_link})"
         else:
             raise ValueError("Error uploading video to Google Drive")
@@ -312,6 +319,7 @@ def process_input(text, txt_file, mp3_file, selected_voice, rate, pitch, keyword
     finally:
         cleanup_temp_files()
 
+# Interfaz Gradio
 with gr.Blocks() as demo:
     gr.Markdown("# Text-to-Video Generator")
     with gr.Row():
@@ -321,7 +329,7 @@ with gr.Blocks() as demo:
             mp3_file_input = gr.File(label="Upload background music (.mp3)", file_types=[".mp3"])
             keyword_input = gr.Textbox(
                 label="Enter keywords separated by commas",
-                value="fear, religion, god, demons, aliens, possession, galaxy, mysterious, dystopian, astral, warfare, space, space, galaxy, moon, fear, astral, god, evil, mystery, cosmos, stars, paranormal, inexplicable, hidden, enigma, unknown, unusual, intriguing, curious, strange, supernatural, esoteric, arcane, occultism, supernatural, mystery, phenomenon, rare, unusual, enigmatic, sinister, gloomy, dark, shadowy, macabre, eerie, chilling, cursed, fantastic, unreal, unknown, mysterious, enigmatic, inexplicable, unusual, strange, unusual, arcane, esoteric, hidden, shadowy, dark, gloomy, sinister, macabre, eerie, chilling, cursed, fantastic, unreal, paranormal, supernatural, occultism, phenomenon, rare, intriguing, curious"
+                value="nature, landscape, city, people"
             )
             voices = asyncio.run(get_voices())
             voice_dropdown = gr.Dropdown(choices=list(voices.keys()), label="Select Voice")