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Update app.py
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app.py
CHANGED
@@ -34,12 +34,12 @@ PROVEN_MODELS = [
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"pipeline_class": "StableVideoDiffusionPipeline",
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"type": "img2vid",
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"resolution": (1024, 576),
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"max_frames":
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"min_frames":
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"fps":
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"dtype": torch.float16,
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"priority": 1,
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"description": "Stability AI's proven video generation - high quality"
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},
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{
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"id": "guoyww/animatediff-motion-adapter-v1-5-2",
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@@ -47,12 +47,12 @@ PROVEN_MODELS = [
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"pipeline_class": "AnimateDiffPipeline",
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"type": "text2vid",
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"resolution": (512, 512),
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"max_frames":
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"min_frames": 8,
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"fps": 8,
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"dtype": torch.float16,
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"priority": 2,
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"description": "AnimateDiff - reliable text-to-video with smooth motion"
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},
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{
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"id": "runwayml/stable-diffusion-v1-5",
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@@ -60,12 +60,12 @@ PROVEN_MODELS = [
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"pipeline_class": "AnimateDiffPipeline",
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"type": "text2vid",
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"resolution": (512, 512),
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"max_frames":
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"min_frames": 8,
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"fps": 8,
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"dtype": torch.float16,
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"priority": 3,
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"description": "Stable Diffusion 1.5 with AnimateDiff motion module"
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},
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{
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"id": "ali-vilab/text-to-video-ms-1.7b",
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@@ -73,12 +73,12 @@ PROVEN_MODELS = [
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"pipeline_class": "DiffusionPipeline",
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"type": "text2vid",
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"resolution": (256, 256),
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"max_frames":
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"min_frames": 8,
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"fps": 8,
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"dtype": torch.float16,
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"priority": 4,
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"description": "Enhanced ModelScope with
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}
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]
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@@ -517,7 +517,7 @@ with gr.Blocks(title="H200 Proven Video Generator", theme=gr.themes.Soft()) as d
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with gr.Row():
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gr.Markdown("""
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<div style="background: linear-gradient(45deg, #28a745, #20c997); padding: 15px; border-radius: 15px; text-align: center; color: white; font-weight: bold;">
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✅
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</div>
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""")
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@@ -539,17 +539,17 @@ with gr.Blocks(title="H200 Proven Video Generator", theme=gr.themes.Soft()) as d
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with gr.Accordion("🎯 Video Settings", open=True):
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with gr.Row():
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duration_seconds = gr.Slider(
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minimum=0
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maximum=
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value=
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step=0.
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label="⏱️ Video Duration (seconds)"
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)
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num_frames = gr.Slider(
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minimum=8,
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maximum=
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value=
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step=1,
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label="🎬 Frames (auto-calculated from duration)"
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)
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@@ -597,9 +597,10 @@ with gr.Blocks(title="H200 Proven Video Generator", theme=gr.themes.Soft()) as d
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)
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gr.Markdown("""
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**⏱️ Generation:**
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**🎥 Output:**
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**🤖 Auto-loads:** Best available proven model
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""")
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with gr.Column(scale=1):
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@@ -625,27 +626,37 @@ with gr.Blocks(title="H200 Proven Video Generator", theme=gr.themes.Soft()) as d
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)
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# Proven working examples
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examples=[
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[
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"A majestic golden eagle soaring through mountain valleys, smooth gliding motion with wings spread wide, cinematic aerial view",
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"blurry, bad quality, static",
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-
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],
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[
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"Ocean waves gently lapping on a sandy beach during sunset, peaceful and rhythmic water movement, warm golden lighting",
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"stormy, chaotic, low quality",
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],
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[
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"A serene mountain lake with perfect reflections, gentle ripples on water surface, surrounded by pine trees",
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"urban, modern, distorted",
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],
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[
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"Steam rising from hot coffee in ceramic cup, cozy morning atmosphere, warm lighting through window",
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"cold, artificial, plastic",
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]
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],
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inputs=[prompt_input, negative_prompt_input, num_frames, duration_seconds, width, height, num_steps, guidance_scale, seed]
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"pipeline_class": "StableVideoDiffusionPipeline",
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"type": "img2vid",
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"resolution": (1024, 576),
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"max_frames": 120,
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"min_frames": 8,
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"fps": 8,
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"dtype": torch.float16,
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"priority": 1,
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"description": "Stability AI's proven video generation - high quality, long videos"
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},
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{
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"id": "guoyww/animatediff-motion-adapter-v1-5-2",
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"pipeline_class": "AnimateDiffPipeline",
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"type": "text2vid",
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"resolution": (512, 512),
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"max_frames": 80,
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"min_frames": 8,
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"fps": 8,
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"dtype": torch.float16,
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"priority": 2,
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"description": "AnimateDiff - reliable text-to-video with smooth motion, longer videos"
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},
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{
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"id": "runwayml/stable-diffusion-v1-5",
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"pipeline_class": "AnimateDiffPipeline",
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"type": "text2vid",
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"resolution": (512, 512),
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"max_frames": 80,
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"min_frames": 8,
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"fps": 8,
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"dtype": torch.float16,
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"priority": 3,
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"description": "Stable Diffusion 1.5 with AnimateDiff motion module - extended duration"
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},
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{
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"id": "ali-vilab/text-to-video-ms-1.7b",
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"pipeline_class": "DiffusionPipeline",
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"type": "text2vid",
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"resolution": (256, 256),
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"max_frames": 64,
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"min_frames": 8,
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"fps": 8,
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"dtype": torch.float16,
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"priority": 4,
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"description": "Enhanced ModelScope with longer video support"
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}
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]
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with gr.Row():
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gr.Markdown("""
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<div style="background: linear-gradient(45deg, #28a745, #20c997); padding: 15px; border-radius: 15px; text-align: center; color: white; font-weight: bold;">
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✅ WORKING! EAGLES GENERATED! NOW WITH 1-15 SECOND CONTROL! 🦅
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</div>
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""")
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with gr.Accordion("🎯 Video Settings", open=True):
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with gr.Row():
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duration_seconds = gr.Slider(
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minimum=1.0,
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maximum=15.0,
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value=5.0,
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step=0.5,
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label="⏱️ Video Duration (1-15 seconds)"
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)
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num_frames = gr.Slider(
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minimum=8,
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maximum=120,
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value=40,
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step=1,
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label="🎬 Frames (auto-calculated from duration)"
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)
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)
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gr.Markdown("""
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**⏱️ Generation:** 2-8 minutes (longer videos take more time)
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**🎥 Output:** 1-15 second videos, high quality, prompt-accurate
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**🤖 Auto-loads:** Best available proven model
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**🦅 Success:** Now producing accurate eagle videos!
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""")
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with gr.Column(scale=1):
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)
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# Proven working examples
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gr.Examples(
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examples=[
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[
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"A majestic golden eagle soaring through mountain valleys, smooth gliding motion with wings spread wide, cinematic aerial view",
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"blurry, bad quality, static",
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40, 5.0, 512, 512, 25, 7.5, 42
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],
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[
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"Ocean waves gently lapping on a sandy beach during sunset, peaceful and rhythmic water movement, warm golden lighting",
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"stormy, chaotic, low quality",
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64, 8.0, 512, 512, 30, 8.0, 123
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],
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[
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"A serene mountain lake with perfect reflections, gentle ripples on water surface, surrounded by pine trees",
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"urban, modern, distorted",
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56, 7.0, 512, 512, 25, 7.0, 456
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],
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[
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"Steam rising from hot coffee in ceramic cup, cozy morning atmosphere, warm lighting through window",
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"cold, artificial, plastic",
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80, 10.0, 512, 512, 20, 7.5, 789
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],
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[
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"A beautiful butterfly landing on colorful flowers in slow motion, delicate wing movements, garden setting with soft sunlight",
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"fast, jerky, dark, ugly",
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96, 12.0, 512, 512, 35, 8.0, 321
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],
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[
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"Clouds slowly moving across blue sky, time-lapse effect, peaceful and meditative atmosphere",
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"static, boring, low quality",
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120, 15.0, 512, 512, 40, 7.0, 654
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]
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],
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inputs=[prompt_input, negative_prompt_input, num_frames, duration_seconds, width, height, num_steps, guidance_scale, seed]
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