Update core/visual_engine.py
Browse files- core/visual_engine.py +69 -94
core/visual_engine.py
CHANGED
@@ -1,6 +1,6 @@
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# core/visual_engine.py
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from PIL import Image, ImageDraw, ImageFont, ImageOps
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import base64
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# --- MONKEY PATCH ---
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try:
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@@ -22,7 +22,7 @@ import io
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import time
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import random
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import logging
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import mimetypes
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logger = logging.getLogger(__name__)
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logger.setLevel(logging.INFO)
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@@ -75,12 +75,8 @@ class VisualEngine:
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self.runway_api_key = None; self.USE_RUNWAYML = False; self.runway_client = None
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if RUNWAYML_SDK_IMPORTED and RunwayMLAPIClient:
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try:
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if os.getenv("RUNWAYML_API_SECRET"):
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logger.info("RunwayML Client initialized using RUNWAYML_API_SECRET env var.")
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# else: # No explicit else, will be handled by set_runway_api_key if key provided later
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except Exception as e_runway_init:
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logger.error(f"Failed to initialize RunwayML client during __init__: {e_runway_init}", exc_info=True)
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logger.info("VisualEngine initialized.")
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@@ -100,17 +96,10 @@ class VisualEngine:
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if RUNWAYML_SDK_IMPORTED and RunwayMLAPIClient:
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if not self.runway_client:
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try:
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if not os.getenv("RUNWAYML_API_SECRET"):
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self.USE_RUNWAYML = True
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logger.info("RunwayML Client initialized successfully via set_runway_api_key.")
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except Exception as e_client_init:
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logger.error(f"RunwayML Client initialization failed in set_runway_api_key: {e_client_init}", exc_info=True)
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self.USE_RUNWAYML = False
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else: # Client already initialized
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self.USE_RUNWAYML = True; logger.info("RunwayML Client was already initialized.")
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else: logger.warning("RunwayML SDK not imported. API key set, but integration requires SDK."); self.USE_RUNWAYML = False
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else: self.USE_RUNWAYML = False; logger.info("RunwayML Disabled (no API key).")
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@@ -128,76 +117,46 @@ class VisualEngine:
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except Exception as e: logger.error(f"Error converting {image_path} to data URI: {e}", exc_info=True); return None
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def _map_resolution_to_runway_ratio(self, width, height):
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ratio_str = f"{width}:{height}"
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supported_ratios = ["1280:720", "720:1280", "1104:832", "832:1104", "960:960", "1584:672"]
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if ratio_str in supported_ratios: return ratio_str
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logger.warning(f"
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return "1280:720"
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def _get_text_dimensions(self,text_content,font_obj):
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# (Corrected version from previous, assuming font_obj.size exists or font_size_pil is fallback)
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default_char_height = getattr(font_obj, 'size', self.font_size_pil)
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if not text_content: return 0, default_char_height
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try:
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if hasattr(font_obj,'getbbox'):
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w,h=font_obj.getsize(text_content)
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return w, h if h > 0 else default_char_height
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else: # Fallback if no standard method (should not happen for ImageFont)
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return int(len(text_content)*default_char_height*0.6),int(default_char_height*1.2)
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except Exception as e:
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logger.warning(f"Error in _get_text_dimensions for '{text_content[:20]}...': {e}")
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return int(len(text_content)*self.font_size_pil*0.6),int(self.font_size_pil*1.2) # Fallback to global default
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def _create_placeholder_image_content(self,text_description,filename,size=None):
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# <<< THIS IS THE CORRECTED METHOD >>>
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if size is None: size = self.video_frame_size
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img=Image.new('RGB',size,color=(20,20,40));d=ImageDraw.Draw(img);padding=25;max_w=size[0]-(2*padding);lines=[];
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if not text_description: text_description="(Placeholder Image)"
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words=text_description.split();current_line=""
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for word_idx, word in enumerate(words):
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# Add space correctly, not after the very last word of the text
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prospective_line_addition = word + (" " if word_idx < len(words) - 1 else "")
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test_line = current_line + prospective_line_addition
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current_line_width, _ = self._get_text_dimensions(test_line, self.font)
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if current_line_width == 0 and test_line.strip():
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current_line =
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if current_line.strip(): # Add previous line if it had content
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lines.append(current_line.strip())
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current_line = prospective_line_addition # Start new line with current word (plus its space if not last)
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# If the word itself is too long for a line, it will just be one long line.
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# Pillow's d.text will handle overflow if text anchor isn't 'lt' (left-top).
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# For centered text, it might go off-canvas; more complex word splitting needed for that.
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if current_line.strip(): # Add any remaining part
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lines.append(current_line.strip())
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if not lines and text_description:
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avg_char_width, _ = self._get_text_dimensions("W", self.font)
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if avg_char_width == 0: avg_char_width = self.font_size_pil * 0.6
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chars_per_line = int(max_w / avg_char_width) if avg_char_width > 0 else 20
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lines.append(text_description[:chars_per_line] + ("..." if len(text_description) > chars_per_line else ""))
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elif not lines:
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lines.append("(Placeholder Error)")
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_,single_line_h=self._get_text_dimensions("Ay",self.font); single_line_h = single_line_h if single_line_h > 0 else self.font_size_pil + 2
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max_lines_to_display=min(len(lines),(size[1]-(2*padding))//(single_line_h+2)) if single_line_h > 0 else 1
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if max_lines_to_display <=0: max_lines_to_display = 1
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y_text_start = padding + (size[1]-(2*padding) - max_lines_to_display*(single_line_h+2))/2.0
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y_text = y_text_start
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for i in range(max_lines_to_display):
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line_content=lines[i]
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line_w,_=self._get_text_dimensions(line_content,self.font)
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if line_w == 0 and line_content.strip(): line_w = len(line_content) * (self.font_size_pil * 0.6)
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x_text=(size[0]-line_w)/2.0
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try: d.text((x_text,y_text),line_content,font=self.font,fill=(200,200,180))
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@@ -211,20 +170,44 @@ class VisualEngine:
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try:img.save(filepath);return filepath
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except Exception as e:logger.error(f"Saving placeholder image {filepath}: {e}", exc_info=True);return None
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def _search_pexels_image(self,
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#
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if not self.USE_PEXELS or not self.pexels_api_key: return None
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def _generate_video_clip_with_runwayml(self, text_prompt_for_motion, input_image_path, scene_identifier_filename_base, target_duration_seconds=5):
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# (Updated RunwayML integration)
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if not self.USE_RUNWAYML or not self.runway_client: logger.warning("RunwayML not enabled/client not init. Skip video."); return None
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if not input_image_path or not os.path.exists(input_image_path): logger.error(f"Runway Gen-4 needs input image. Path invalid: {input_image_path}"); return None
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image_data_uri = self._image_to_data_uri(input_image_path)
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@@ -237,7 +220,7 @@ class VisualEngine:
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try:
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task = self.runway_client.image_to_video.create(model='gen4_turbo', prompt_image=image_data_uri, prompt_text=text_prompt_for_motion, duration=runway_duration, ratio=runway_ratio_str)
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logger.info(f"Runway Gen-4 task ID: {task.id}. Polling...")
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poll_interval=10; max_polls=36
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for _ in range(max_polls):
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time.sleep(poll_interval); task_details = self.runway_client.tasks.retrieve(id=task.id)
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logger.info(f"Runway task {task.id} status: {task_details.status}")
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@@ -258,7 +241,7 @@ class VisualEngine:
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except AttributeError as ae: logger.error(f"RunwayML SDK AttributeError: {ae}. SDK/methods might differ.", exc_info=True); return None
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except Exception as e: logger.error(f"Runway Gen-4 API error: {e}", exc_info=True); return None
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def _create_placeholder_video_content(self, td, fn, dur=4, sz=None):
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if sz is None: sz = self.video_frame_size; fp = os.path.join(self.output_dir, fn); tc = None
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try: tc = TextClip(td, fontsize=50, color='white', font=self.video_overlay_font, bg_color='black', size=sz, method='caption').set_duration(dur); tc.write_videofile(fp, fps=24, codec='libx264', preset='ultrafast', logger=None, threads=2); logger.info(f"Generic placeholder video: {fp}"); return fp
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except Exception as e: logger.error(f"Generic placeholder video error {fp}: {e}", exc_info=True); return None
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@@ -268,15 +251,13 @@ class VisualEngine:
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def generate_scene_asset(self, image_generation_prompt_text, motion_prompt_text_for_video,
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scene_data, scene_identifier_filename_base,
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generate_as_video_clip=False, runway_target_duration=5):
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# (Logic mostly as before, ensuring base image is robustly generated first)
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base_name, _ = os.path.splitext(scene_identifier_filename_base)
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asset_info = {'path': None, 'type': 'none', 'error': True, 'prompt_used': image_generation_prompt_text, 'error_message': 'Asset generation init failed'}
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input_image_for_runway_path = None
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base_image_filename = base_name + ("_base_for_video.png" if generate_as_video_clip else ".png")
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base_image_filepath = os.path.join(self.output_dir, base_image_filename)
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if self.USE_AI_IMAGE_GENERATION and self.openai_api_key: # DALL-E
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max_r, att_n = 2,0;
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for att_n in range(max_r):
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try:logger.info(f"Att {att_n+1} DALL-E (base img): {image_generation_prompt_text[:70]}...");cl=openai.OpenAI(api_key=self.openai_api_key,timeout=90.0);r=cl.images.generate(model=self.dalle_model,prompt=image_generation_prompt_text,n=1,size=self.image_size_dalle3,quality="hd",response_format="url",style="vivid");iu=r.data[0].url;rp=getattr(r.data[0],'revised_prompt',None);
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except Exception as e:logger.error(f"DALL-E base img error:{e}",exc_info=True);asset_info['error_message']=str(e);break
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if asset_info['error']:logger.warning(f"DALL-E failed after {att_n+1} attempts for base img.")
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if asset_info['error'] and self.USE_PEXELS:
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logger.info("Trying Pexels for base img.");pqt=scene_data.get('pexels_search_query_감독',f"{scene_data.get('emotional_beat','')} {scene_data.get('setting_description','')}");pp=self._search_pexels_image(pqt,base_image_filename);
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if pp:input_image_for_runway_path=pp;asset_info={'path':pp,'type':'image','error':False,'prompt_used':f"Pexels:{pqt}"}
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else:current_em=asset_info.get('error_message',"");asset_info['error_message']=(current_em+" Pexels failed for base.").strip()
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if asset_info['error']:
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logger.warning("Base img (DALL-E/Pexels) failed. Using placeholder.");ppt=asset_info.get('prompt_used',image_generation_prompt_text);php=self._create_placeholder_image_content(f"[Base Placeholder]{ppt[:70]}...",base_image_filename);
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if php:input_image_for_runway_path=php;asset_info={'path':php,'type':'image','error':False,'prompt_used':ppt}
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else:current_em=asset_info.get('error_message',"");asset_info['error_message']=(current_em+" Base placeholder failed.").strip()
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if generate_as_video_clip:
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if not input_image_for_runway_path:logger.error("RunwayML video: base img failed.");asset_info['error']=True;asset_info['error_message']=(asset_info.get('error_message',"")+" Base img miss, Runway abort.").strip();asset_info['type']='none';return asset_info
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if self.USE_RUNWAYML:
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logger.info(f"Runway Gen-4 video for {base_name} using base: {input_image_for_runway_path}")
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if video_path and os.path.exists(video_path):asset_info={'path':video_path,'type':'video','error':False,'prompt_used':motion_prompt_text_for_video,'base_image_path':input_image_for_runway_path}
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else:logger.warning(f"RunwayML video failed for {base_name}. Fallback to base img.");asset_info['error']=True;asset_info['error_message']=(asset_info.get('error_message',"Base img ok.")+" RunwayML video fail; use base img.").strip();asset_info['path']=input_image_for_runway_path;asset_info['type']='image';asset_info['prompt_used']=image_generation_prompt_text
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else:logger.warning("RunwayML selected but disabled. Use base img.");asset_info['error']=True;asset_info['error_message']=(asset_info.get('error_message',"Base img ok.")+" RunwayML disabled; use base img.").strip();asset_info['path']=input_image_for_runway_path;asset_info['type']='image';asset_info['prompt_used']=image_generation_prompt_text
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return asset_info
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def generate_narration_audio(self, text_to_narrate, output_filename="narration_overall.mp3"):
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# (Keep as before)
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if not self.USE_ELEVENLABS or not self.elevenlabs_client or not text_to_narrate: logger.info("11L skip."); return None; afp=os.path.join(self.output_dir,output_filename)
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try: logger.info(f"11L audio (Voice:{self.elevenlabs_voice_id}): {text_to_narrate[:70]}..."); asm=None
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if hasattr(self.elevenlabs_client,'text_to_speech')and hasattr(self.elevenlabs_client.text_to_speech,'stream'):asm=self.elevenlabs_client.text_to_speech.stream;logger.info("Using 11L .text_to_speech.stream()")
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logger.info(f"11L audio (stream): {afp}");return afp
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except Exception as e:logger.error(f"11L audio error: {e}",exc_info=True);return None
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def assemble_animatic_from_assets(self, asset_data_list, overall_narration_path=None, output_filename="final_video.mp4", fps=24):
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# (Keep as in the version that has the robust image processing, C-contiguous array, and debug image saves)
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if not asset_data_list: logger.warning("No assets for animatic."); return None
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processed_clips = []; narration_clip = None; final_clip = None
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logger.info(f"Assembling from {len(asset_data_list)} assets. Frame: {self.video_frame_size}.")
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for i, asset_info in enumerate(asset_data_list):
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asset_path, asset_type, scene_dur = asset_info.get('path'), asset_info.get('type'), asset_info.get('duration', 4.5)
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scene_num, key_action = asset_info.get('scene_num', i + 1), asset_info.get('key_action', '')
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logger.info(f"S{scene_num}: Path='{asset_path}', Type='{asset_type}', Dur='{scene_dur}'s")
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if not (asset_path and os.path.exists(asset_path)): logger.warning(f"S{scene_num}: Not found '{asset_path}'. Skip."); continue
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if scene_dur <= 0: logger.warning(f"S{scene_num}: Invalid duration ({scene_dur}s). Skip."); continue
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current_scene_mvpy_clip = None
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try:
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if asset_type == 'image':
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else:
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if scene_dur/src_clip.duration > 1.5 and src_clip.duration>0.1:tmp_clip=src_clip.loop(duration=scene_dur)
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else:tmp_clip=src_clip.set_duration(src_clip.duration);logger.info(f"S{scene_num} Video clip ({src_clip.duration:.2f}s) shorter than target ({scene_dur:.2f}s).")
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current_scene_mvpy_clip=tmp_clip.set_duration(scene_dur)
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if current_scene_mvpy_clip.size!=list(self.video_frame_size):current_scene_mvpy_clip=current_scene_mvpy_clip.resize(self.video_frame_size)
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except Exception as e:logger.error(f"S{scene_num} Video load error '{asset_path}':{e}",exc_info=True);continue
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finally:
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except Exception as e:logger.error(f"Video write error:{e}",exc_info=True);return None
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finally:
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logger.debug("Closing all MoviePy clips in `assemble_animatic_from_assets` finally block.")
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all_clips_to_close = processed_clips + ([narration_clip] if narration_clip else []) + ([final_clip] if final_clip else [])
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for clip_obj_to_close in all_clips_to_close:
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if clip_obj_to_close and hasattr(clip_obj_to_close, 'close'):
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try: clip_obj_to_close.close()
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# core/visual_engine.py
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from PIL import Image, ImageDraw, ImageFont, ImageOps
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import base64
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# --- MONKEY PATCH ---
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try:
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import time
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import random
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import logging
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import mimetypes
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logger = logging.getLogger(__name__)
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logger.setLevel(logging.INFO)
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self.runway_api_key = None; self.USE_RUNWAYML = False; self.runway_client = None
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if RUNWAYML_SDK_IMPORTED and RunwayMLAPIClient:
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try:
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if os.getenv("RUNWAYML_API_SECRET"): self.runway_client = RunwayMLAPIClient(); logger.info("RunwayML Client initialized using RUNWAYML_API_SECRET env var.")
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except Exception as e_runway_init: logger.error(f"Failed to initialize RunwayML client during __init__: {e_runway_init}", exc_info=True)
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logger.info("VisualEngine initialized.")
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if RUNWAYML_SDK_IMPORTED and RunwayMLAPIClient:
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if not self.runway_client:
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try:
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if not os.getenv("RUNWAYML_API_SECRET"): os.environ["RUNWAYML_API_SECRET"] = k; logger.info("Setting RUNWAYML_API_SECRET env var from provided key.")
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self.runway_client = RunwayMLAPIClient(); self.USE_RUNWAYML = True; logger.info("RunwayML Client initialized successfully via set_runway_api_key.")
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except Exception as e_client_init: logger.error(f"RunwayML Client init failed in set_runway_api_key: {e_client_init}", exc_info=True); self.USE_RUNWAYML = False
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else: self.USE_RUNWAYML = True; logger.info("RunwayML Client was already initialized.")
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else: logger.warning("RunwayML SDK not imported. API key set, but integration requires SDK."); self.USE_RUNWAYML = False
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else: self.USE_RUNWAYML = False; logger.info("RunwayML Disabled (no API key).")
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except Exception as e: logger.error(f"Error converting {image_path} to data URI: {e}", exc_info=True); return None
|
118 |
|
119 |
def _map_resolution_to_runway_ratio(self, width, height):
|
120 |
+
ratio_str = f"{width}:{height}"; supported_ratios = ["1280:720", "720:1280", "1104:832", "832:1104", "960:960", "1584:672"]
|
|
|
|
|
121 |
if ratio_str in supported_ratios: return ratio_str
|
122 |
+
logger.warning(f"Res {ratio_str} not directly Gen-4 supported. Default 1280:720."); return "1280:720"
|
|
|
123 |
|
124 |
def _get_text_dimensions(self,text_content,font_obj):
|
|
|
125 |
default_char_height = getattr(font_obj, 'size', self.font_size_pil)
|
126 |
if not text_content: return 0, default_char_height
|
127 |
try:
|
128 |
+
if hasattr(font_obj,'getbbox'): bbox=font_obj.getbbox(text_content);w=bbox[2]-bbox[0];h=bbox[3]-bbox[1]; return w, h if h > 0 else default_char_height
|
129 |
+
elif hasattr(font_obj,'getsize'): w,h=font_obj.getsize(text_content); return w, h if h > 0 else default_char_height
|
130 |
+
else: return int(len(text_content)*default_char_height*0.6),int(default_char_height*1.2)
|
131 |
+
except Exception as e: logger.warning(f"Error in _get_text_dimensions: {e}"); return int(len(text_content)*self.font_size_pil*0.6),int(self.font_size_pil*1.2)
|
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|
132 |
|
133 |
def _create_placeholder_image_content(self,text_description,filename,size=None):
|
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|
134 |
if size is None: size = self.video_frame_size
|
135 |
img=Image.new('RGB',size,color=(20,20,40));d=ImageDraw.Draw(img);padding=25;max_w=size[0]-(2*padding);lines=[];
|
136 |
if not text_description: text_description="(Placeholder Image)"
|
137 |
words=text_description.split();current_line=""
|
138 |
for word_idx, word in enumerate(words):
|
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|
139 |
prospective_line_addition = word + (" " if word_idx < len(words) - 1 else "")
|
140 |
test_line = current_line + prospective_line_addition
|
|
|
141 |
current_line_width, _ = self._get_text_dimensions(test_line, self.font)
|
142 |
+
if current_line_width == 0 and test_line.strip(): current_line_width = len(test_line) * (self.font_size_pil * 0.6)
|
143 |
+
if current_line_width <= max_w: current_line = test_line
|
144 |
+
else:
|
145 |
+
if current_line.strip(): lines.append(current_line.strip())
|
146 |
+
current_line = prospective_line_addition
|
147 |
+
if current_line.strip(): lines.append(current_line.strip())
|
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|
148 |
if not lines and text_description:
|
149 |
avg_char_width, _ = self._get_text_dimensions("W", self.font)
|
150 |
+
if avg_char_width == 0: avg_char_width = self.font_size_pil * 0.6
|
151 |
chars_per_line = int(max_w / avg_char_width) if avg_char_width > 0 else 20
|
152 |
lines.append(text_description[:chars_per_line] + ("..." if len(text_description) > chars_per_line else ""))
|
153 |
+
elif not lines: lines.append("(Placeholder Error)")
|
|
|
|
|
154 |
_,single_line_h=self._get_text_dimensions("Ay",self.font); single_line_h = single_line_h if single_line_h > 0 else self.font_size_pil + 2
|
155 |
max_lines_to_display=min(len(lines),(size[1]-(2*padding))//(single_line_h+2)) if single_line_h > 0 else 1
|
156 |
if max_lines_to_display <=0: max_lines_to_display = 1
|
157 |
+
y_text_start = padding + (size[1]-(2*padding) - max_lines_to_display*(single_line_h+2))/2.0; y_text = y_text_start
|
|
|
|
|
|
|
158 |
for i in range(max_lines_to_display):
|
159 |
+
line_content=lines[i]; line_w,_=self._get_text_dimensions(line_content,self.font)
|
|
|
160 |
if line_w == 0 and line_content.strip(): line_w = len(line_content) * (self.font_size_pil * 0.6)
|
161 |
x_text=(size[0]-line_w)/2.0
|
162 |
try: d.text((x_text,y_text),line_content,font=self.font,fill=(200,200,180))
|
|
|
170 |
try:img.save(filepath);return filepath
|
171 |
except Exception as e:logger.error(f"Saving placeholder image {filepath}: {e}", exc_info=True);return None
|
172 |
|
173 |
+
def _search_pexels_image(self, query, output_filename_base):
|
174 |
+
# <<< CORRECTED METHOD >>>
|
175 |
+
if not self.USE_PEXELS or not self.pexels_api_key: return None
|
176 |
+
headers = {"Authorization": self.pexels_api_key}
|
177 |
+
params = {"query": query, "per_page": 1, "orientation": "landscape", "size": "large2x"}
|
178 |
+
pexels_filename = output_filename_base.replace(".png", f"_pexels_{random.randint(1000,9999)}.jpg").replace(".mp4", f"_pexels_{random.randint(1000,9999)}.jpg")
|
179 |
+
filepath = os.path.join(self.output_dir, pexels_filename)
|
180 |
+
try:
|
181 |
+
logger.info(f"Pexels search: '{query}'")
|
182 |
+
effective_query = " ".join(query.split()[:5])
|
183 |
+
params["query"] = effective_query
|
184 |
+
response = requests.get("https://api.pexels.com/v1/search", headers=headers, params=params, timeout=20)
|
185 |
+
response.raise_for_status()
|
186 |
+
data = response.json()
|
187 |
+
if data.get("photos") and len(data["photos"]) > 0:
|
188 |
+
photo_url = data["photos"][0]["src"]["large2x"]
|
189 |
+
image_response = requests.get(photo_url, timeout=60)
|
190 |
+
image_response.raise_for_status()
|
191 |
+
img_data = Image.open(io.BytesIO(image_response.content))
|
192 |
+
if img_data.mode != 'RGB':
|
193 |
+
img_data = img_data.convert('RGB')
|
194 |
+
img_data.save(filepath)
|
195 |
+
logger.info(f"Pexels image saved: {filepath}")
|
196 |
+
return filepath
|
197 |
+
else:
|
198 |
+
logger.info(f"No photos found on Pexels for query: '{effective_query}'")
|
199 |
+
return None # Added explicit return
|
200 |
+
except requests.exceptions.RequestException as e_req:
|
201 |
+
logger.error(f"Pexels request error for query '{query}': {e_req}", exc_info=True)
|
202 |
+
except json.JSONDecodeError as e_json:
|
203 |
+
logger.error(f"Pexels JSON decode error for query '{query}': {e_json}", exc_info=True)
|
204 |
+
except IOError as e_io:
|
205 |
+
logger.error(f"Pexels image save error for query '{query}': {e_io}", exc_info=True)
|
206 |
+
except Exception as e:
|
207 |
+
logger.error(f"Unexpected Pexels error for query '{query}': {e}", exc_info=True)
|
208 |
+
return None # Ensure None is returned on any exception
|
209 |
|
210 |
def _generate_video_clip_with_runwayml(self, text_prompt_for_motion, input_image_path, scene_identifier_filename_base, target_duration_seconds=5):
|
|
|
211 |
if not self.USE_RUNWAYML or not self.runway_client: logger.warning("RunwayML not enabled/client not init. Skip video."); return None
|
212 |
if not input_image_path or not os.path.exists(input_image_path): logger.error(f"Runway Gen-4 needs input image. Path invalid: {input_image_path}"); return None
|
213 |
image_data_uri = self._image_to_data_uri(input_image_path)
|
|
|
220 |
try:
|
221 |
task = self.runway_client.image_to_video.create(model='gen4_turbo', prompt_image=image_data_uri, prompt_text=text_prompt_for_motion, duration=runway_duration, ratio=runway_ratio_str)
|
222 |
logger.info(f"Runway Gen-4 task ID: {task.id}. Polling...")
|
223 |
+
poll_interval=10; max_polls=36
|
224 |
for _ in range(max_polls):
|
225 |
time.sleep(poll_interval); task_details = self.runway_client.tasks.retrieve(id=task.id)
|
226 |
logger.info(f"Runway task {task.id} status: {task_details.status}")
|
|
|
241 |
except AttributeError as ae: logger.error(f"RunwayML SDK AttributeError: {ae}. SDK/methods might differ.", exc_info=True); return None
|
242 |
except Exception as e: logger.error(f"Runway Gen-4 API error: {e}", exc_info=True); return None
|
243 |
|
244 |
+
def _create_placeholder_video_content(self, td, fn, dur=4, sz=None):
|
245 |
if sz is None: sz = self.video_frame_size; fp = os.path.join(self.output_dir, fn); tc = None
|
246 |
try: tc = TextClip(td, fontsize=50, color='white', font=self.video_overlay_font, bg_color='black', size=sz, method='caption').set_duration(dur); tc.write_videofile(fp, fps=24, codec='libx264', preset='ultrafast', logger=None, threads=2); logger.info(f"Generic placeholder video: {fp}"); return fp
|
247 |
except Exception as e: logger.error(f"Generic placeholder video error {fp}: {e}", exc_info=True); return None
|
|
|
251 |
def generate_scene_asset(self, image_generation_prompt_text, motion_prompt_text_for_video,
|
252 |
scene_data, scene_identifier_filename_base,
|
253 |
generate_as_video_clip=False, runway_target_duration=5):
|
|
|
254 |
base_name, _ = os.path.splitext(scene_identifier_filename_base)
|
255 |
asset_info = {'path': None, 'type': 'none', 'error': True, 'prompt_used': image_generation_prompt_text, 'error_message': 'Asset generation init failed'}
|
256 |
input_image_for_runway_path = None
|
257 |
base_image_filename = base_name + ("_base_for_video.png" if generate_as_video_clip else ".png")
|
258 |
base_image_filepath = os.path.join(self.output_dir, base_image_filename)
|
259 |
|
260 |
+
if self.USE_AI_IMAGE_GENERATION and self.openai_api_key:
|
|
|
261 |
max_r, att_n = 2,0;
|
262 |
for att_n in range(max_r):
|
263 |
try:logger.info(f"Att {att_n+1} DALL-E (base img): {image_generation_prompt_text[:70]}...");cl=openai.OpenAI(api_key=self.openai_api_key,timeout=90.0);r=cl.images.generate(model=self.dalle_model,prompt=image_generation_prompt_text,n=1,size=self.image_size_dalle3,quality="hd",response_format="url",style="vivid");iu=r.data[0].url;rp=getattr(r.data[0],'revised_prompt',None);
|
|
|
267 |
except Exception as e:logger.error(f"DALL-E base img error:{e}",exc_info=True);asset_info['error_message']=str(e);break
|
268 |
if asset_info['error']:logger.warning(f"DALL-E failed after {att_n+1} attempts for base img.")
|
269 |
|
270 |
+
if asset_info['error'] and self.USE_PEXELS:
|
271 |
logger.info("Trying Pexels for base img.");pqt=scene_data.get('pexels_search_query_감독',f"{scene_data.get('emotional_beat','')} {scene_data.get('setting_description','')}");pp=self._search_pexels_image(pqt,base_image_filename);
|
272 |
if pp:input_image_for_runway_path=pp;asset_info={'path':pp,'type':'image','error':False,'prompt_used':f"Pexels:{pqt}"}
|
273 |
else:current_em=asset_info.get('error_message',"");asset_info['error_message']=(current_em+" Pexels failed for base.").strip()
|
274 |
|
275 |
+
if asset_info['error']:
|
276 |
logger.warning("Base img (DALL-E/Pexels) failed. Using placeholder.");ppt=asset_info.get('prompt_used',image_generation_prompt_text);php=self._create_placeholder_image_content(f"[Base Placeholder]{ppt[:70]}...",base_image_filename);
|
277 |
if php:input_image_for_runway_path=php;asset_info={'path':php,'type':'image','error':False,'prompt_used':ppt}
|
278 |
else:current_em=asset_info.get('error_message',"");asset_info['error_message']=(current_em+" Base placeholder failed.").strip()
|
279 |
|
280 |
+
if generate_as_video_clip:
|
281 |
if not input_image_for_runway_path:logger.error("RunwayML video: base img failed.");asset_info['error']=True;asset_info['error_message']=(asset_info.get('error_message',"")+" Base img miss, Runway abort.").strip();asset_info['type']='none';return asset_info
|
282 |
if self.USE_RUNWAYML:
|
283 |
logger.info(f"Runway Gen-4 video for {base_name} using base: {input_image_for_runway_path}")
|
|
|
285 |
if video_path and os.path.exists(video_path):asset_info={'path':video_path,'type':'video','error':False,'prompt_used':motion_prompt_text_for_video,'base_image_path':input_image_for_runway_path}
|
286 |
else:logger.warning(f"RunwayML video failed for {base_name}. Fallback to base img.");asset_info['error']=True;asset_info['error_message']=(asset_info.get('error_message',"Base img ok.")+" RunwayML video fail; use base img.").strip();asset_info['path']=input_image_for_runway_path;asset_info['type']='image';asset_info['prompt_used']=image_generation_prompt_text
|
287 |
else:logger.warning("RunwayML selected but disabled. Use base img.");asset_info['error']=True;asset_info['error_message']=(asset_info.get('error_message',"Base img ok.")+" RunwayML disabled; use base img.").strip();asset_info['path']=input_image_for_runway_path;asset_info['type']='image';asset_info['prompt_used']=image_generation_prompt_text
|
288 |
+
return asset_info
|
289 |
|
290 |
def generate_narration_audio(self, text_to_narrate, output_filename="narration_overall.mp3"):
|
|
|
291 |
if not self.USE_ELEVENLABS or not self.elevenlabs_client or not text_to_narrate: logger.info("11L skip."); return None; afp=os.path.join(self.output_dir,output_filename)
|
292 |
try: logger.info(f"11L audio (Voice:{self.elevenlabs_voice_id}): {text_to_narrate[:70]}..."); asm=None
|
293 |
if hasattr(self.elevenlabs_client,'text_to_speech')and hasattr(self.elevenlabs_client.text_to_speech,'stream'):asm=self.elevenlabs_client.text_to_speech.stream;logger.info("Using 11L .text_to_speech.stream()")
|
|
|
307 |
logger.info(f"11L audio (stream): {afp}");return afp
|
308 |
except Exception as e:logger.error(f"11L audio error: {e}",exc_info=True);return None
|
309 |
|
|
|
310 |
def assemble_animatic_from_assets(self, asset_data_list, overall_narration_path=None, output_filename="final_video.mp4", fps=24):
|
|
|
311 |
if not asset_data_list: logger.warning("No assets for animatic."); return None
|
312 |
processed_clips = []; narration_clip = None; final_clip = None
|
313 |
logger.info(f"Assembling from {len(asset_data_list)} assets. Frame: {self.video_frame_size}.")
|
|
|
314 |
for i, asset_info in enumerate(asset_data_list):
|
315 |
asset_path, asset_type, scene_dur = asset_info.get('path'), asset_info.get('type'), asset_info.get('duration', 4.5)
|
316 |
scene_num, key_action = asset_info.get('scene_num', i + 1), asset_info.get('key_action', '')
|
317 |
logger.info(f"S{scene_num}: Path='{asset_path}', Type='{asset_type}', Dur='{scene_dur}'s")
|
|
|
318 |
if not (asset_path and os.path.exists(asset_path)): logger.warning(f"S{scene_num}: Not found '{asset_path}'. Skip."); continue
|
319 |
if scene_dur <= 0: logger.warning(f"S{scene_num}: Invalid duration ({scene_dur}s). Skip."); continue
|
|
|
320 |
current_scene_mvpy_clip = None
|
321 |
try:
|
322 |
if asset_type == 'image':
|
|
|
347 |
else:
|
348 |
if scene_dur/src_clip.duration > 1.5 and src_clip.duration>0.1:tmp_clip=src_clip.loop(duration=scene_dur)
|
349 |
else:tmp_clip=src_clip.set_duration(src_clip.duration);logger.info(f"S{scene_num} Video clip ({src_clip.duration:.2f}s) shorter than target ({scene_dur:.2f}s).")
|
350 |
+
current_scene_mvpy_clip=tmp_clip.set_duration(scene_dur)
|
351 |
if current_scene_mvpy_clip.size!=list(self.video_frame_size):current_scene_mvpy_clip=current_scene_mvpy_clip.resize(self.video_frame_size)
|
352 |
except Exception as e:logger.error(f"S{scene_num} Video load error '{asset_path}':{e}",exc_info=True);continue
|
353 |
finally:
|
|
|
393 |
except Exception as e:logger.error(f"Video write error:{e}",exc_info=True);return None
|
394 |
finally:
|
395 |
logger.debug("Closing all MoviePy clips in `assemble_animatic_from_assets` finally block.")
|
396 |
+
all_clips_to_close = processed_clips + ([narration_clip] if narration_clip else []) + ([final_clip] if final_clip else [])
|
397 |
for clip_obj_to_close in all_clips_to_close:
|
398 |
if clip_obj_to_close and hasattr(clip_obj_to_close, 'close'):
|
399 |
try: clip_obj_to_close.close()
|