Create app.py

app.py

@@ -0,0 +1,117 @@
+import gradio as gr
+import torch
+from diffusers import StableDiffusionPipeline
+import os
+import uuid
+import animation_logic as anim
+import video_utils as vid
+
+# --- Model Config (SDXS Optimized) ---
+device = "cpu"
+model_id = "IDKiro/sdxs-512-dreamshaper"
+pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float32)
+pipe.to(device)
+
+def run_deforum(
+    prompt_list_str, neg_prompt, max_frames, 
+    zoom_str, angle_str, tx_str, ty_str,
+    cadence, fps
+):
+    # Setup
+    width, height = 256, 256
+    try:
+        prompts = eval(prompt_list_str)
+    except:
+        return None, None, "Error: Prompt dictionary format invalid."
+
+    # Parse Schedules
+    zoom_s = anim.parse_keyframe_string(zoom_str, max_frames)
+    angle_s = anim.parse_keyframe_string(angle_str, max_frames)
+    tx_s = anim.parse_keyframe_string(tx_str, max_frames)
+    ty_s = anim.parse_keyframe_string(ty_str, max_frames)
+    
+    all_frames = []
+    prev_gen_frame = None
+    
+    # Generation Loop
+    for f in range(max_frames):
+        if f % cadence == 0:
+            # Determine prompt
+            current_prompt = prompts[max(k for k in prompts.keys() if k <= f)]
+            
+            # Warp previous frame if it exists
+            if prev_gen_frame is not None:
+                # We warp the frame based on the cumulative motion across the cadence gap
+                init_image = anim.anim_frame_warp(prev_gen_frame, angle_s[f], zoom_s[f], tx_s[f], ty_s[f])
+                # SDXS Inference (1-step, 0 guidance)
+                new_frame = pipe(
+                    current_prompt, 
+                    image=init_image, # This mimics the 'strength' logic
+                    negative_prompt=neg_prompt,
+                    num_inference_steps=1,
+                    guidance_scale=0.0,
+                    width=width, height=height
+                ).images[0]
+            else:
+                # First frame
+                new_frame = pipe(
+                    current_prompt, 
+                    negative_prompt=neg_prompt,
+                    num_inference_steps=1,
+                    guidance_scale=0.0,
+                    width=width, height=height
+                ).images[0]
+
+            # Handle Cadence Interpolation for the gap behind us
+            if cadence > 1 and prev_gen_frame is not None:
+                start_gap = f - cadence
+                for i in range(1, cadence):
+                    alpha = i / cadence
+                    interp_frame = anim.lerp_frames(prev_gen_frame, new_frame, alpha)
+                    all_frames.append(interp_frame)
+            
+            all_frames.append(new_frame)
+            prev_gen_frame = new_frame
+            yield new_frame, None, None
+            
+    # Finalize Video and Zip
+    video_file = vid.frames_to_video(all_frames, f"output_{uuid.uuid4().hex[:6]}.mp4", fps)
+    zip_file = vid.export_to_zip(all_frames, f"frames_{uuid.uuid4().hex[:6]}.zip")
+    
+    yield all_frames[-1], video_file, zip_file
+
+# --- Gradio Interface ---
+with gr.Blocks(theme=gr.themes.Glass()) as demo:
+    gr.Markdown("# 🎨 Deforum Soonr Variant 2")
+    
+    with gr.Row():
+        with gr.Column(scale=1):
+            prompts = gr.Textbox(label="Prompts (Frame: Prompt Dict)", 
+                                 value='{0: "a snowy mountain", 15: "a fiery volcano"}', lines=3)
+            neg_p = gr.Textbox(label="Negative Prompt", value="blur, lowres, text")
+            
+            with gr.Row():
+                frames_n = gr.Number(label="Max Frames", value=20)
+                cadence_n = gr.Slider(1, 4, value=2, step=1, label="Cadence (Skip Steps)")
+                fps_n = gr.Number(label="FPS", value=10)
+            
+            with gr.Accordion("Motion Parameters", open=False):
+                zoom = gr.Textbox(label="Zoom", value="0:(1.04)")
+                angle = gr.Textbox(label="Angle", value="0:(2*sin(t/5))")
+                tx = gr.Textbox(label="Translation X", value="0:(0)")
+                ty = gr.Textbox(label="Translation Y", value="0:(0)")
+            
+            btn = gr.Button("Generate", variant="primary")
+            
+        with gr.Column(scale=1):
+            preview = gr.Image(label="Live Frame Preview")
+            video_out = gr.Video(label="Rendered Animation")
+            file_out = gr.File(label="Download Batch (ZIP)")
+
+    btn.click(
+        fn=run_deforum,
+        inputs=[prompts, neg_p, frames_n, zoom, angle, tx, ty, cadence_n, fps_n],
+        outputs=[preview, video_out, file_out]
+    )
+
+demo.launch()