Update app.py
Browse files
app.py
CHANGED
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@@ -5,49 +5,31 @@ from diffusers.utils import export_to_video
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import uuid
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import os
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# Model Tanımlama
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model_id = "vdo/zeroscope_v2_576w"
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# Pipeline Hazırlığı
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print("Patron komedi dükkanını açıyoruz, model yükleniyor...")
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pipe = DiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float32)
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pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)
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pipe.to("cpu")
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print("Motor hazır, kahkahalar için emirlerini bekliyorum!")
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def generate_video(prompt):
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try:
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#
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# num_inference_steps=
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# num_frames=
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#
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frames = pipe(
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prompt,
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num_inference_steps=
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height=
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width=
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num_frames=
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).frames
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# Her video için benzersiz isim
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unique_name = f"viral_{uuid.uuid4()}.mp4"
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# Video dışa aktarımı (FPS 10 yaparak hareketi hızlandırdık, daha komik durur)
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export_to_video(frames[0], unique_name, fps=10)
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return os.path.abspath(unique_name)
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except Exception as e:
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print(f"HATA
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return None
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demo = gr.Interface(
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inputs=gr.Textbox(label="Viral Video Prompt"),
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outputs=gr.Video(label="Funny Result"),
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api_name="predict"
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)
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if __name__ == "__main__":
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demo.launch()
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import uuid
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import os
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model_id = "vdo/zeroscope_v2_576w"
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pipe = DiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float32)
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pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)
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pipe.to("cpu")
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def generate_video(prompt):
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try:
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# KALİTEYİ MAKSİMUMA ÇIKARDIK:
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# num_inference_steps=25 (Şekiller netleşecek)
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# num_frames=24 (Video 3 saniye olacak)
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# Çözünürlüğü biraz daha artırdık
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frames = pipe(
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prompt,
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num_inference_steps=25,
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height=320,
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width=576,
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num_frames=24
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).frames
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unique_name = f"viral_{uuid.uuid4()}.mp4"
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export_to_video(frames[0], unique_name, fps=8)
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return os.path.abspath(unique_name)
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except Exception as e:
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print(f"HATA: {e}")
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return None
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demo = gr.Interface(fn=generate_video, inputs="text", outputs="video", api_name="predict")
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demo.launch()
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