backup

2026-05-15 18:02:38 +02:00
parent 72016728e2
commit 307e452251
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+"""Hero reel v4 — 6 precise shots."""
+import os, sys, time, subprocess
+
+try:
+    from google import genai
+    from google.genai import types
+except ImportError:
+    os.system(f"{sys.executable} -m pip install google-genai --quiet")
+    from google import genai
+    from google.genai import types
+
+API_KEY  = os.environ.get("GEMINI_API_KEY", "AIzaSyB_1p8KvaT_rdNJGPs8HKk8bKsvUlcL6Kg")
+BASE_DIR = os.path.dirname(os.path.dirname(__file__))
+VID_DIR  = os.path.join(BASE_DIR, "assets", "videos", "hero", "clips")
+REEL_OUT = os.path.join(BASE_DIR, "assets", "videos", "hero", "hero-reel.mp4")
+os.makedirs(VID_DIR, exist_ok=True)
+client   = genai.Client(api_key=API_KEY)
+
+SHOTS = [
+    {
+        "name": "v4-shot-01",
+        "prompt": (
+            "Medium cinematic shot. A family — two adults and two children — walks through a front door "
+            "into a residential home. The camera follows their feet as they step onto the beige carpet "
+            "in the entryway, then slowly pans down to show their shoes leaving dirty tracks on the carpet. "
+            "Warm afternoon light. Photorealistic, slow motion."
+        ),
+    },
+    {
+        "name": "v4-shot-02",
+        "prompt": (
+            "Slow-motion close-up cinematic shot. A wine glass tips over on a light grey fabric sofa cushion. "
+            "Red wine pours out of the glass and spreads across the sofa cushion, soaking into the fabric. "
+            "The dark red stain expands slowly across the grey upholstery. "
+            "Warm living room light. No people visible. Photorealistic, dramatic slow motion."
+        ),
+    },
+    {
+        "name": "v4-shot-03",
+        "prompt": (
+            "Cinematic close-up shot slowly pushing in on a section of heavily soiled residential carpet. "
+            "The beige carpet has multiple visible stains — dark spots, discoloration, pet stains, "
+            "and general dirt buildup embedded in the fibers. "
+            "Dramatic side lighting emphasizes the depth of the stains. No people. No equipment. Photorealistic."
+        ),
+    },
+    {
+        "name": "v4-shot-04",
+        "prompt": (
+            "Close-up cinematic shot. A carpet cleaning technician in a plain black shirt pushes "
+            "a large upright carpet cleaning machine — like a Rug Doctor — across a dirty beige carpet. "
+            "Tight shot focused on the wide flat cleaning head at the base of the machine pressing against "
+            "the carpet and moving forward. The carpet behind the machine looks visibly cleaner and brighter. "
+            "The machine only pulls dirt and moisture INTO itself — nothing comes out. "
+            "No steam. No liquid leaving the machine. Photorealistic slow motion."
+        ),
+    },
+    {
+        "name": "v4-shot-05",
+        "prompt": (
+            "Wide cinematic shot slowly pushing forward through the main entrance of a modern commercial "
+            "office building. Clean grey carpet covers the entire lobby floor. Glass doors, white walls, "
+            "professional overhead lighting. The carpet is the visual centerpiece — clean, uniform, well-maintained. "
+            "No people. No machines. Photorealistic."
+        ),
+    },
+    {
+        "name": "v4-shot-06",
+        "prompt": (
+            "Cinematic wide shot inside a bright clean residential living room. "
+            "The camera slowly pans upward from the clean plush beige carpet to reveal the whole room. "
+            "A family — two adults and a child — walks in at different moments and relaxes on the sofa. "
+            "Everyone is wearing socks. The carpet is spotless and fluffy. Warm natural light. "
+            "Comfortable, inviting atmosphere. Photorealistic."
+        ),
+    },
+]
+
+MODELS = ["veo-3.1-generate-preview", "veo-2.0-generate-001"]
+
+def poll(op, timeout=600):
+    elapsed = 0
+    while not op.done:
+        if elapsed >= timeout:
+            return None
+        print(f"  Waiting... ({elapsed}s)")
+        time.sleep(15)
+        elapsed += 15
+        op = client.operations.get(op)
+    return op
+
+saved = []
+for i, item in enumerate(SHOTS):
+    out_path = os.path.join(VID_DIR, f"{item['name']}.mp4")
+    print(f"\n[{i+1}/{len(SHOTS)}] {item['name']}...")
+    done = False
+    for model in MODELS:
+        try:
+            print(f"  Trying {model}...")
+            op = client.models.generate_videos(
+                model=model,
+                prompt=item["prompt"],
+                config=types.GenerateVideosConfig(
+                    aspect_ratio="16:9", resolution="720p",
+                    duration_seconds=6, number_of_videos=1,
+                ),
+            )
+            op = poll(op)
+            if op and op.response and op.response.generated_videos:
+                vid = op.response.generated_videos[0].video
+                video_bytes = client.files.download(file=vid)
+                if video_bytes:
+                    with open(out_path, "wb") as f:
+                        f.write(video_bytes)
+                    print(f"  Saved ({os.path.getsize(out_path)//1024}KB)")
+                    saved.append(out_path)
+                    done = True
+                    break
+                else:
+                    try:
+                        vid.save(out_path)
+                        print(f"  Saved via .save()")
+                        saved.append(out_path)
+                        done = True
+                        break
+                    except Exception as e2:
+                        print(f"  Download failed: {e2}")
+            else:
+                print(f"  No video returned from {model}")
+        except Exception as e:
+            print(f"  Error with {model}: {e}")
+    if not done:
+        print(f"  FAILED: {item['name']}")
+
+print(f"\n{len(saved)}/{len(SHOTS)} shots saved")
+
+if len(saved) >= 2:
+    clips = [os.path.join(VID_DIR, f"{s['name']}.mp4") for s in SHOTS
+             if os.path.exists(os.path.join(VID_DIR, f"{s['name']}.mp4"))]
+    concat_file = os.path.join(VID_DIR, "concat-v4.txt")
+    with open(concat_file, "w") as f:
+        for p in clips:
+            f.write(f"file '{p}'\n")
+    result = subprocess.run(
+        ["ffmpeg", "-y", "-f", "concat", "-safe", "0", "-i", concat_file,
+         "-c:v", "libx264", "-crf", "22", "-preset", "fast", "-movflags", "+faststart", REEL_OUT],
+        capture_output=True, text=True
+    )
+    if result.returncode == 0:
+        print(f"  Reel saved ({os.path.getsize(REEL_OUT)//1024}KB)")
+    else:
+        print(f"  ffmpeg error: {result.stderr[-300:]}")
+
+print("\nDone.")