backup

2026-05-15 18:02:38 +02:00
parent 72016728e2
commit 307e452251
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+"""
+Hero reel v3 — 7 shots with corrected prompts.
+"""
+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": "v3-shot-01",
+        "prompt": (
+            "Medium shot. A family of four — two adults and two children — walks through the front door "
+            "of a warm residential home. Camera is inside the home facing them as they enter. "
+            "After they walk in, the camera slowly pans down to the carpet, revealing dirty footprints "
+            "and mud tracked onto the beige carpet. Warm natural light. Photorealistic."
+        ),
+    },
+    {
+        "name": "v3-shot-02",
+        "prompt": (
+            "Medium shot, slow zoom in. A glass of red wine has spilled onto a light grey upholstered sofa. "
+            "The camera starts wide on the sofa then slowly zooms in on the dark wine stain spreading "
+            "across the fabric. The stain is clearly visible, soaked into the cushion. "
+            "Warm living room light. No people. Photorealistic."
+        ),
+    },
+    {
+        "name": "v3-shot-03",
+        "prompt": (
+            "Medium shot at low angle, camera near floor level. Inside a bright commercial office entryway. "
+            "A person wearing work boots walks through the entry door toward the camera and past it. "
+            "The camera is low, showing the boots and lower legs as they walk across the carpet past the lens. "
+            "Office carpet visible, natural light from glass doors behind. Photorealistic."
+        ),
+    },
+    {
+        "name": "v3-shot-04",
+        "prompt": (
+            "Close-up cinematic shot. A technician's gloved hand holds a small upholstery extraction wand — "
+            "a flat rectangular handheld tool. The technician presses the wand firmly onto a wine-stained "
+            "sofa cushion and draws it slowly across the fabric. The stain visibly lifts as the wand moves. "
+            "Suction only — no water sprays out. Slow motion. Natural light. Photorealistic."
+        ),
+    },
+    {
+        "name": "v3-shot-05",
+        "prompt": (
+            "Wide cinematic shot. Camera slowly pans across the entrance of a modern commercial office building. "
+            "Clean grey commercial carpet stretches across the lobby floor. Large windows, glass doors, "
+            "professional lighting. The carpet looks freshly cleaned and spotless. "
+            "No people. No machines. Photorealistic."
+        ),
+    },
+    {
+        "name": "v3-shot-06",
+        "prompt": (
+            "Wide cinematic shot. Camera slowly pans across a bright, clean residential living room. "
+            "Plush clean beige carpet throughout. Comfortable furniture — sofa, armchairs, coffee table. "
+            "Warm natural afternoon light through large windows. The room looks fresh and inviting. "
+            "No people. No cleaning equipment. Photorealistic."
+        ),
+    },
+    {
+        "name": "v3-shot-07",
+        "prompt": (
+            "Wide cinematic shot. Camera moves slowly forward through an upscale restaurant dining room. "
+            "Rich carpet covers the floor. White tablecloths, warm ambient lighting, wood accents. "
+            "The carpet looks clean, deep, and well-maintained as the camera glides through the space. "
+            "No people. Photorealistic, luxurious atmosphere."
+        ),
+    },
+]
+
+MODEL = "veo-3.1-generate-preview"
+
+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']}...")
+    try:
+        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)
+            else:
+                try:
+                    vid.save(out_path)
+                    print(f"  Saved via .save()")
+                    saved.append(out_path)
+                except Exception as e2:
+                    print(f"  Download failed: {e2}")
+        else:
+            print(f"  No video returned")
+    except Exception as e:
+        print(f"  Error: {e}")
+
+print(f"\n{len(saved)}/{len(SHOTS)} shots saved")
+
+if len(saved) >= 2:
+    concat_file = os.path.join(VID_DIR, "concat-v3.txt")
+    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"))]
+    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.")