""" Generate all site images via FLUX.1 Schnell GGUF through ComfyUI. FLUX Schnell: 4 steps, cfg=1.0, no negative prompt, photorealistic. Run after ComfyUI restart: python3 tools/gen-images-flux.py """ import json, time, urllib.request, os, random, io COMFY = "http://localhost:8188" HERO_DIR = os.path.join(os.path.dirname(os.path.dirname(__file__)), "assets", "images", "hero") SVC_DIR = os.path.join(os.path.dirname(os.path.dirname(__file__)), "assets", "images", "services") IMAGES = [ # --- HERO IMAGES --- {"filename": "hero-carpet-cleaning.jpg", "dir": HERO_DIR, "prompt": ( "low-angle 35mm lens perspective looking across thick plush cream carpet in an upstate New York living room, " "carpet fibers razor sharp in foreground, couch and coffee table receding into shallow bokeh background, " "warm afternoon window light raking across carpet texture, Finger Lakes farmhouse interior, " "no people, ultra-realistic architectural photography, 16:9" )}, {"filename": "hero-stairs.jpg", "dir": HERO_DIR, "prompt": ( "dramatic low 35mm angle looking up a clean carpeted staircase from floor level, " "light grey carpet runner sharp and textured in foreground steps, wood banister receding diagonally, " "bright daylight flooding from above, shallow depth of field, " "no people, ultra-realistic interior photography, 16:9" )}, {"filename": "hero-upholstery.jpg", "dir": HERO_DIR, "prompt": ( "50mm lens low corner angle across a bright residential living room, " "plush linen fabric sofa arm sharp in near foreground, clean armchair and window receding with bokeh, " "afternoon countryside light through window, shallow depth of field, " "no people, ultra-realistic interior photography, 16:9" )}, {"filename": "hero-floors.jpg", "dir": HERO_DIR, "prompt": ( "low 24mm angle pressed to gleaming light oak hardwood floor, " "floor grain razor sharp in extreme foreground receding to hallway vanishing point, " "white walls, natural light streaming in, shallow depth of field, " "no people, ultra-realistic interior photography, 16:9" )}, {"filename": "hero-area-rugs.jpg", "dir": HERO_DIR, "prompt": ( "low 35mm angle looking across a hand-knotted oriental rug from floor level, " "rich red and gold rug fibers sharp in foreground, hardwood floor and room receding into bokeh, " "cozy farmhouse living room, warm natural light, shallow depth of field, " "no people, ultra-realistic interior photography, 16:9" )}, {"filename": "hero-add-ons.jpg", "dir": HERO_DIR, "prompt": ( "low 35mm angle across a clean beige bedroom carpet, " "carpet pile sharp and detailed in near foreground, wooden bed frame and sheer curtained window receding, " "crisp morning light, shallow depth of field, " "no people, no machines, ultra-realistic interior photography, 16:9" )}, {"filename": "hero-commercial.jpg", "dir": HERO_DIR, "prompt": ( "low 24mm wide-angle lens across a modern corporate lobby floor, " "dark charcoal commercial carpet sharp in extreme foreground receding to glass entrance doors, " "recessed ceiling lights creating depth, strong vanishing point perspective, " "no people, ultra-realistic architectural photography, 16:9" )}, {"filename": "hero-offices.jpg", "dir": HERO_DIR, "prompt": ( "low 24mm angle across clean grey carpet tiles in a modern open-plan office, " "carpet tile seams sharp in foreground receding to rows of empty desks and glass partitions, " "professional overhead lighting, strong linear perspective, " "no people, ultra-realistic architectural photography, 16:9" )}, {"filename": "hero-vacation-rentals.jpg", "dir": HERO_DIR, "prompt": ( "low 35mm angle across clean beige carpet in a Finger Lakes cottage living room, " "carpet fibers sharp in foreground, stone fireplace and lake-view window receding with bokeh, " "wooden ceiling beams, warm inviting light, shallow depth of field, " "no people, ultra-realistic interior photography, 16:9" )}, {"filename": "hero-hotels.jpg", "dir": HERO_DIR, "prompt": ( "low 24mm lens looking down a long hotel corridor from floor level, " "patterned burgundy carpet runner sharp in extreme foreground receding to vanishing point, " "warm wall sconces lining white walls, numbered doors converging in perspective, " "no people, ultra-realistic hospitality photography, 16:9" )}, {"filename": "hero-retail.jpg", "dir": HERO_DIR, "prompt": ( "low 35mm diagonal angle across clean light grey carpet in an upscale retail showroom, " "carpet surface sharp in foreground, minimalist display fixtures and storefront windows receding with bokeh, " "bright track lighting overhead, shallow depth of field, " "no people, ultra-realistic architectural photography, 16:9" )}, {"filename": "hero-property-management.jpg", "dir": HERO_DIR, "prompt": ( "low 35mm angle across fresh neutral carpet in an empty move-in ready apartment, " "carpet texture sharp in foreground, bare white walls and bright windows receding, " "clean real estate photography perspective, shallow depth of field, " "no people, ultra-realistic real estate photography, 16:9" )}, {"filename": "hero-about.jpg", "dir": HERO_DIR, "prompt": ( "low 35mm angle from lawn level looking up at a classic upstate New York suburban home, " "green grass blades sharp in extreme foreground, inviting house facade receding upward, " "mature trees and clear blue sky, warm summer afternoon, " "no people, ultra-realistic real estate photography, 16:9" )}, {"filename": "hero-service-area.jpg", "dir": HERO_DIR, "prompt": ( "low horizon 24mm wide-angle Finger Lakes landscape, " "green vineyard vines sharp in foreground receding to rolling hills and calm lake, " "golden hour light casting long shadows, strong depth and distance, " "no people, ultra-realistic landscape photography, 16:9" )}, {"filename": "hero-living-room.jpg", "dir": HERO_DIR, "prompt": ( "low 35mm corner angle across a spacious residential living room, " "plush light grey carpet sharp and textured in foreground, large sectional sofa and bay windows receding with bokeh, " "warm afternoon sunlight, shallow depth of field, " "no people, ultra-realistic interior photography, 16:9" )}, {"filename": "hero-clean-result.jpg", "dir": HERO_DIR, "prompt": ( "extreme low 50mm macro angle pressed to immaculate freshly cleaned residential carpet, " "individual carpet fibers razor sharp in foreground, pile receding into soft bokeh, " "raking natural light revealing deep clean texture and uniform pile height, " "no people, ultra-realistic macro carpet photography, 16:9" )}, # --- SERVICE CARD IMAGES --- {"filename": "carpet-cleaning.jpg", "dir": SVC_DIR, "prompt": ( "low 35mm angle looking across plush clean beige carpet in a residential living room, " "carpet fibers sharp in foreground, couch and window receding into bokeh, " "warm afternoon light, shallow depth of field, no people, ultra-realistic interior photography" )}, {"filename": "stairs-cleaning.jpg", "dir": SVC_DIR, "prompt": ( "low 35mm angle looking up clean grey carpeted stairs from bottom step, " "carpet texture sharp on nearest step, stairs receding diagonally upward, " "wood banister, bright light from above, no people, ultra-realistic interior photography" )}, {"filename": "upholstery-cleaning.jpg", "dir": SVC_DIR, "prompt": ( "low 50mm angle across a clean plush linen fabric sofa arm, " "fabric weave sharp in foreground, living room receding with bokeh, " "warm light, shallow depth of field, no people, ultra-realistic interior photography" )}, {"filename": "floor-cleaning.jpg", "dir": SVC_DIR, "prompt": ( "low 24mm angle pressed to gleaming light oak hardwood floor, " "wood grain razor sharp in extreme foreground receding down hallway, " "natural light, no people, ultra-realistic interior photography" )}, {"filename": "area-rug-cleaning.jpg", "dir": SVC_DIR, "prompt": ( "low 35mm angle across a vibrant clean oriental rug from floor level, " "rug fibers and pattern sharp in foreground, hardwood floor and room receding, " "warm light, shallow depth of field, no people, ultra-realistic interior photography" )}, {"filename": "add-ons.jpg", "dir": SVC_DIR, "prompt": ( "low 35mm angle across clean beige bedroom carpet, " "carpet pile sharp in foreground, bed frame and curtained window receding with bokeh, " "morning light, no people, ultra-realistic interior photography" )}, {"filename": "commercial-overview.jpg", "dir": SVC_DIR, "prompt": ( "low 24mm angle across dark commercial carpet in a corporate lobby, " "carpet surface sharp in foreground receding to glass entrance, " "strong vanishing point, no people, ultra-realistic architectural photography" )}, {"filename": "vacation-rentals.jpg", "dir": SVC_DIR, "prompt": ( "low 35mm angle across clean carpet in a Finger Lakes cottage living room, " "carpet sharp in foreground, stone fireplace and window receding with bokeh, " "rustic warm decor, no people, ultra-realistic interior photography" )}, {"filename": "office-spaces.jpg", "dir": SVC_DIR, "prompt": ( "low 24mm angle across grey carpet tiles in a modern open office, " "tile seams sharp in foreground, empty desks receding with linear perspective, " "professional lighting, no people, ultra-realistic architectural photography" )}, {"filename": "hotels-inns.jpg", "dir": SVC_DIR, "prompt": ( "low 24mm angle down a hotel corridor, patterned carpet runner sharp in foreground, " "corridor receding to vanishing point, warm wall sconces, " "no people, ultra-realistic hospitality photography" )}, {"filename": "retail-showrooms.jpg", "dir": SVC_DIR, "prompt": ( "low 35mm diagonal angle across light grey carpet in an upscale retail showroom, " "carpet sharp in foreground, display fixtures and track lighting receding with bokeh, " "no people, ultra-realistic architectural photography" )}, {"filename": "property-management.jpg", "dir": SVC_DIR, "prompt": ( "low 35mm angle across fresh neutral carpet in an empty clean apartment, " "carpet texture sharp in foreground, white walls and windows receding, " "no people, ultra-realistic real estate photography" )}, ] def build_workflow(prompt, seed=None): if seed is None: seed = random.randint(0, 2**32) return { "1": { "class_type": "UnetLoaderGGUF", "inputs": {"unet_name": "flux1-schnell-Q8_0.gguf"}, }, "2": { "class_type": "DualCLIPLoader", "inputs": { "clip_name1": "t5xxl_fp8_e4m3fn.safetensors", "clip_name2": "clip_l.safetensors", "type": "flux", }, }, "3": { "class_type": "VAELoader", "inputs": {"vae_name": "ae.safetensors"}, }, "4": { "class_type": "CLIPTextEncode", "inputs": {"clip": ["2", 0], "text": prompt}, }, "5": { "class_type": "EmptyLatentImage", "inputs": {"batch_size": 1, "height": 576, "width": 1024}, }, "6": { "class_type": "KSampler", "inputs": { "cfg": 1.0, "denoise": 1.0, "latent_image": ["5", 0], "model": ["1", 0], "negative": ["4", 0], "positive": ["4", 0], "sampler_name": "euler", "scheduler": "simple", "seed": seed, "steps": 4, }, }, "7": { "class_type": "VAEDecode", "inputs": {"samples": ["6", 0], "vae": ["3", 0]}, }, "8": { "class_type": "SaveImage", "inputs": {"filename_prefix": "flux_lahr", "images": ["7", 0]}, }, } def queue_prompt(workflow): data = json.dumps({"prompt": workflow}).encode() req = urllib.request.Request( f"{COMFY}/prompt", data=data, headers={"Content-Type": "application/json"} ) with urllib.request.urlopen(req) as resp: return json.loads(resp.read())["prompt_id"] def wait_for_result(prompt_id, timeout=600): start = time.time() while time.time() - start < timeout: try: with urllib.request.urlopen(f"{COMFY}/history/{prompt_id}") as resp: hist = json.loads(resp.read()) if prompt_id in hist: entry = hist[prompt_id] status = entry.get("status", {}).get("status_str", "") if status == "error": msgs = entry.get("status", {}).get("messages", []) print(f" COMFYUI ERROR: {msgs}", flush=True) return None for node_out in entry.get("outputs", {}).values(): if "images" in node_out: return node_out["images"] except Exception: pass time.sleep(5) return None def download_image(img_info, out_path): fname = img_info["filename"] subfolder = img_info.get("subfolder", "") img_type = img_info.get("type", "output") url = f"{COMFY}/view?filename={fname}&subfolder={subfolder}&type={img_type}" with urllib.request.urlopen(url) as resp: data = resp.read() try: from PIL import Image img = Image.open(io.BytesIO(data)).convert("RGB") img.save(out_path, "JPEG", quality=92) print(f" OK: {os.path.basename(out_path)} ({os.path.getsize(out_path)//1024}KB)", flush=True) except ImportError: png_path = out_path.replace(".jpg", ".png") with open(png_path, "wb") as f: f.write(data) print(f" OK (PNG): {png_path}", flush=True) total = len(IMAGES) for i, spec in enumerate(IMAGES): out_path = os.path.join(spec["dir"], spec["filename"]) print(f"\n[{i+1}/{total}] {spec['filename']}", flush=True) workflow = build_workflow(spec["prompt"]) prompt_id = queue_prompt(workflow) print(f" queued {prompt_id[:8]}...", flush=True) images = wait_for_result(prompt_id) if images: download_image(images[0], out_path) else: print(f" FAILED (timeout)", flush=True) print("\nAll done.", flush=True)