simplification and prompt bugfix

gradio_ui.py

@@ -24,7 +24,7 @@ import torch
 from tqdm.auto import tqdm
 from PIL import Image
 import torch
-from movie_util import MovieSaver
+from movie_util import MovieSaver, concatenate_movies
 from typing import Callable, List, Optional, Union
 from latent_blending import get_time, yml_save, LatentBlending, add_frames_linear_interp, compare_dicts
 from stable_diffusion_holder import StableDiffusionHolder
@@ -33,12 +33,6 @@ import gradio as gr
 import copy
 
 
-"""
-try this:
-    button variant 'primary' for main call-to-action, 'secondary' for a more subdued style
-    gr.Column(scale=1, min_width=600):
-
-"""
 
 #%%
 
@@ -62,17 +56,19 @@ class BlendingFrontend():
         self.prompt2 = ""
         self.negative_prompt = ""
         self.list_settings = []
-        self.state_prev = {}
         self.state_current = {}
         self.showing_current = True
         self.branch1_influence = 0.02
-        self.imgs_show_last = []
-        self.imgs_show_current = []
         self.nmb_branches_final = 9
         self.nmb_imgs_show = 5 # don't change
         self.fps = 30
         self.duration = 10
-        self.max_size_imgs = 200 # gradio otherwise mega slow 
+        self.dict_multi_trans = {}
+        self.dict_multi_trans_include = {}
+        self.multi_trans_currently_shown = []
+        self.list_fp_imgs_current = []
+        self.current_timestamp = None
+        self.nmb_trans_stack = 8
         
         if not self.use_debug:
             self.lb.sdh.num_inference_steps = self.num_inference_steps
@@ -82,6 +78,10 @@ class BlendingFrontend():
             self.height = 768
             self.width = 768
         
+        # make dummy image
+        self.fp_img_empty = 'empty.jpg'
+        Image.fromarray(np.zeros((self.height, self.width, 3), dtype=np.uint8)).save(self.fp_img_empty, quality=5)
+        
     def change_depth_strength(self, value):
         self.depth_strength = value
         print(f"changed depth_strength to {value}")
@@ -127,14 +127,6 @@ class BlendingFrontend():
         self.fps  = value
         print(f"changed fps to {value}")
         
-    def change_prompt1(self, value):
-        self.prompt1 = value
-        # print(f"changed prompt1 to {value}")
-        
-    def change_prompt2(self, value):
-        self.prompt2 = value
-        # print(f"changed prompt2 to {value}")
-        
     def change_negative_prompt(self, value):
         self.negative_prompt = value
         
@@ -157,30 +149,25 @@ class BlendingFrontend():
         return seed
         
     
-    def run(self):
+    def compute_transition(self, prompt1, prompt2):
+        self.prompt1 = prompt1
+        self.prompt2 = prompt2
         print("STARTING DIFFUSION!")
-        self.state_prev = self.state_current.copy()
         self.state_current = self.get_state_dict()
-        # Copy last iteration
-        self.imgs_show_last = copy.deepcopy(self.imgs_show_current)
-        
         if self.use_debug:
             list_imgs = [(255*np.random.rand(self.height,self.width,3)).astype(np.uint8) for l in range(5)]
             list_imgs = [Image.fromarray(l) for l in list_imgs]
-            list_imgs = self.downscale_imgs(list_imgs)
-            self.imgs_show_current = copy.deepcopy(list_imgs)
             print("DONE! SENDING BACK RESULTS")
             return list_imgs
         
+        # Collect latent blending variables
         self.lb.set_width(self.width)
         self.lb.set_height(self.height)
-        
         self.lb.autosetup_branching(
                 depth_strength = self.depth_strength,
                 num_inference_steps = self.num_inference_steps,
                 nmb_branches_final = self.nmb_branches_final,
                 nmb_mindist = 3)
-        
         self.lb.set_prompt1(self.prompt1)
         self.lb.set_prompt2(self.prompt2)
         self.lb.set_negative_prompt(self.negative_prompt)
@@ -189,31 +176,32 @@ class BlendingFrontend():
         self.lb.guidance_scale_mid_damper = self.guidance_scale_mid_damper
         self.lb.mid_compression_scaler = self.mid_compression_scaler
         self.lb.branch1_influence = self.branch1_influence
-        
         fixed_seeds = [self.seed1, self.seed2]
+        
+        # Run Latent Blending
         imgs_transition = self.lb.run_transition(fixed_seeds=fixed_seeds)
+        print(f"Latent Blending pass finished. Resulted in {len(imgs_transition)} images")
         
-        print(f"DONE DIFFUSION! Resulted in {len(imgs_transition)} images")
+        # Subselect the preview images (hard fixed to self.nmb_imgs_show=5)
-        
         assert np.mod((self.nmb_branches_final-self.nmb_imgs_show)/4, 1)==0, 'self.nmb_branches_final illegal value!'
         idx_list = np.linspace(0, self.nmb_branches_final-1, self.nmb_imgs_show).astype(np.int32)
         list_imgs_preview = []
         for j in idx_list:
             list_imgs_preview.append(Image.fromarray(imgs_transition[j]))
             
-        # Save as jpgs on disk so we are not sending umcompressed data around
+        # Save the preview imgs as jpgs on disk so we are not sending umcompressed data around
-        timestamp = get_time('second')
+        self.current_timestamp = get_time('second')
-        list_fp_imgs = []
+        self.list_fp_imgs_current = []
         for i in range(len(list_imgs_preview)):
-            fp_img = f"img_preview_{i}_{timestamp}.jpg"
+            fp_img = f"img_preview_{i}_{self.current_timestamp}.jpg"
             list_imgs_preview[i].save(fp_img)
-            list_fp_imgs.append(fp_img)
+            self.list_fp_imgs_current.append(fp_img)
         
-        # Save the movie as well
+        # Insert cheap frames for the movie
         imgs_transition_ext = add_frames_linear_interp(imgs_transition, self.duration, self.fps)
 
         # Save as movie
-        fp_movie = f"movie_{timestamp}.mp4"
+        fp_movie = self.get_fp_movie(self.current_timestamp)
         if os.path.isfile(fp_movie):
             os.remove(fp_movie)
         ms = MovieSaver(fp_movie, fps=self.fps)
@@ -221,11 +209,49 @@ class BlendingFrontend():
             ms.write_frame(img)
         ms.finalize()
         print("DONE SAVING MOVIE! SENDING BACK...")
-        list_return = list_fp_imgs + [fp_movie]
-        return list_return
-    
-
         
+        # Assemble Output, updating the preview images and le movie
+        list_return = self.list_fp_imgs_current + [fp_movie]
+        return list_return
+
+    def get_fp_movie(self, timestamp, is_stacked=False):
+        if not is_stacked:
+            return f"movie_{timestamp}.mp4"
+        else:
+            return f"movie_stacked_{timestamp}.mp4"
+            
+    
+    def stack_forward(self, prompt2, seed2):
+        # Save preview images, prompts and seeds into dictionary for stacking
+        self.dict_multi_trans[self.current_timestamp] = generate_list_output(self.prompt1, self.prompt2, self.seed1, self.seed2, self.list_fp_imgs_current)
+        self.dict_multi_trans_include[self.current_timestamp] = True
+        
+        self.lb.swap_forward()
+        list_out = [self.list_fp_imgs_current[-1]]
+        list_out.extend([self.fp_img_empty]*4)
+        list_out.append(prompt2)
+        list_out.append(seed2)
+        list_out.append("")
+        list_out.append(np.random.randint(0, 10000000))
+        
+        list_out_multi_tab = self.update_trans_stacks()
+        
+        list_out.extend(list_out_multi_tab)
+        # self.nmb_trans_stack = len(self.dict_multi_trans_include)
+        return list_out
+
+    def stack_movie(self):
+        # collect all that are in...
+        list_fp_movies = []
+        for timestamp in self.multi_trans_currently_shown:
+            if timestamp is not None:
+                list_fp_movies.append(self.get_fp_movie(timestamp))
+        
+        fp_stacked = self.get_fp_movie(get_time('second'), True)
+        concatenate_movies(fp_stacked, list_fp_movies)
+        return fp_stacked
+        
+
     def get_state_dict(self):
         state_dict = {}
         grab_vars = ['prompt1', 'prompt2', 'seed1', 'seed2', 'height', 'width',
@@ -235,17 +261,77 @@ class BlendingFrontend():
         for v in grab_vars:
             state_dict[v] = getattr(self, v)
         return state_dict
+    
+    
+    def update_trans_stacks(self):
+        print("Updating transition stack...")
         
+        self.multi_trans_currently_shown = []
+        list_output = []
+        # Figure out which transitions should be shown
+        for timestamp in self.dict_multi_trans_include.keys():
+            if len(self.multi_trans_currently_shown) >= self.nmb_trans_stack:
+                continue
+            
+            if self.dict_multi_trans_include[timestamp]:
+                last_timestamp_vals = self.dict_multi_trans[timestamp]
+                list_output.extend(self.dict_multi_trans[timestamp])
+                self.multi_trans_currently_shown.append(timestamp)
+                print(f"including timestamp: {timestamp}")
+        
+        # Fill with empty images if below nmb_trans_stack
+        nmb_empty_missing = self.nmb_trans_stack - len(self.multi_trans_currently_shown)
+        for i in range(nmb_empty_missing):
+            list_output.extend([gr.update(visible=False)]*len(last_timestamp_vals))
+            self.multi_trans_currently_shown.append(None)
+        
+        return list_output
+        
+
+    def remove_trans(self, idx_row):
+        idx_row = int(idx_row)
+        # do removal...
+        if idx_row < len(self.multi_trans_currently_shown):
+            timestamp = self.multi_trans_currently_shown[idx_row]
+            if timestamp in self.dict_multi_trans_include.keys():
+                self.dict_multi_trans_include[timestamp] = False
+                print(f"remove_trans called: {timestamp}")
+        else:
+            print(f"remove_trans called: idx_row too large {idx_row}")
+            
+        return self.update_trans_stacks()
+
+def get_img_rand():
+    return (255*np.random.rand(self.height,self.width,3)).astype(np.uint8)
+
+def generate_list_output(
+        prompt1,
+        prompt2,
+        seed1,
+        seed2,
+        list_fp_imgs,
+        ):
+    list_output = []
+    list_output.append(prompt1)
+    list_output.append(prompt2)
+    list_output.append(seed1)
+    list_output.append(seed2)
+    for fp_img in list_fp_imgs:
+        list_output.append(fp_img)
+    
+    return list_output
+
+
         
 if __name__ == "__main__":    
     
-    fp_ckpt = "../stable_diffusion_models/ckpt/v2-1_768-ema-pruned.ckpt" 
+    # fp_ckpt = "../stable_diffusion_models/ckpt/v2-1_768-ema-pruned.ckpt" 
-    # fp_ckpt = "../stable_diffusion_models/ckpt/v2-1_512-ema-pruned.ckpt" 
+    fp_ckpt = "../stable_diffusion_models/ckpt/v2-1_512-ema-pruned.ckpt" 
-    # sdh = StableDiffusionHolder(fp_ckpt)
+    sdh = StableDiffusionHolder(fp_ckpt)
-    self = BlendingFrontend(None)
+    
+    self = BlendingFrontend(sdh) # Yes this is possible in python and yes it is an awesome trick
     
     with gr.Blocks() as demo:
-        
         with gr.Row():
             prompt1 = gr.Textbox(label="prompt 1")
             prompt2 = gr.Textbox(label="prompt 2")
@@ -265,16 +351,15 @@ if __name__ == "__main__":
             depth_strength = gr.Slider(0.01, 0.99, self.depth_strength, step=0.01, label='depth_strength', interactive=True) 
             duration = gr.Slider(0.1, 30, self.duration, step=0.1, label='video duration', interactive=True) 
             guidance_scale_mid_damper = gr.Slider(0.01, 2.0, self.guidance_scale_mid_damper, step=0.01, label='guidance_scale_mid_damper', interactive=True) 
-                
+            
         with gr.Row():
-            b_run = gr.Button('COMPUTE!', variant='primary')
             seed1 = gr.Number(42, label="seed 1", interactive=True)
+            b_newseed1 = gr.Button("randomize seed 1", variant='secondary')
             seed2 = gr.Number(420, label="seed 2", interactive=True)
-            
+            b_newseed2 = gr.Button("randomize seed 2", variant='secondary')
-            with gr.Column():
+        with gr.Row():
-                b_newseed1 = gr.Button("randomize \nseed 1", variant='secondary')
+            b_compute_transition = gr.Button('compute transition', variant='primary')
-                b_newseed2 = gr.Button("randomize \nseed 2", variant='secondary')
+        
-            
         with gr.Row():
             img1 = gr.Image(label="1/5")
             img2 = gr.Image(label="2/5")
@@ -283,7 +368,7 @@ if __name__ == "__main__":
             img5 = gr.Image(label="5/5")
         
         with gr.Row():
-            vid = gr.Video()
+            vid_transition = gr.Video()
         
         # Bind the on-change methods
         depth_strength.change(fn=self.change_depth_strength, inputs=depth_strength)
@@ -295,8 +380,6 @@ if __name__ == "__main__":
         
         height.change(fn=self.change_height, inputs=height)
         width.change(fn=self.change_width, inputs=width)
-        prompt1.change(fn=self.change_prompt1, inputs=prompt1)
-        prompt2.change(fn=self.change_prompt2, inputs=prompt2)
         negative_prompt.change(fn=self.change_negative_prompt, inputs=negative_prompt)
         seed1.change(fn=self.change_seed1, inputs=seed1)
         seed2.change(fn=self.change_seed2, inputs=seed2)
@@ -305,6 +388,13 @@ if __name__ == "__main__":
     
         b_newseed1.click(self.randomize_seed1, outputs=seed1)
         b_newseed2.click(self.randomize_seed2, outputs=seed2)
-        b_run.click(self.run, outputs=[img1, img2, img3, img4, img5, vid])
+        # b_stackforward.click(self.stack_forward, 
-    
+        #                      inputs=[prompt2, seed2], 
+        #                      outputs=[img1, img2, img3, img4, img5, prompt1, seed1, prompt2])
+        b_compute_transition.click(self.compute_transition, 
+                                   inputs=[prompt1, prompt2],
+                                   outputs=[img1, img2, img3, img4, img5, vid_transition])
+        
+
+
     demo.launch(share=self.share, inbrowser=True, inline=False)