multi transition movies

gradio_ui.py

@@ -56,9 +56,7 @@ class BlendingFrontend():
         self.prompt1 = ""
         self.prompt2 = ""
         self.negative_prompt = ""
-        self.list_settings = []
         self.state_current = {}
-        self.showing_current = True
         self.branch1_influence = 0.3
         self.branch1_max_depth_influence = 0.6
         self.branch1_influence_decay = 0.3
@@ -70,12 +68,10 @@ class BlendingFrontend():
         self.fps = 30
         self.duration_video = 10
         self.t_compute_max_allowed = 10
-        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
+        self.recycle_img1 = False
+        self.recycle_img2 = False
         
         if not self.use_debug:
             self.lb.sdh.num_inference_steps = self.num_inference_steps
@@ -125,7 +121,7 @@ class BlendingFrontend():
         self.lb.set_negative_prompt(list_ui_elem[list_ui_keys.index('negative_prompt')])
         self.lb.guidance_scale = list_ui_elem[list_ui_keys.index('guidance_scale')]
         self.lb.guidance_scale_mid_damper = list_ui_elem[list_ui_keys.index('guidance_scale_mid_damper')]
-        self.lb.t_compute_max_allowed = list_ui_elem[list_ui_keys.index('duration_compute')]
+        self.t_compute_max_allowed = list_ui_elem[list_ui_keys.index('duration_compute')]
         self.lb.num_inference_steps = list_ui_elem[list_ui_keys.index('num_inference_steps')]
         self.lb.sdh.num_inference_steps = list_ui_elem[list_ui_keys.index('num_inference_steps')]
         self.duration_video = list_ui_elem[list_ui_keys.index('duration_video')]
@@ -148,6 +144,8 @@ class BlendingFrontend():
         img1 = Image.fromarray(self.lb.compute_latents1(return_image=True))
         img1.save(fp_img1)
         self.save_empty_image()
+        self.recycle_img1 = True
+        self.recycle_img2 = False
         return [fp_img1, self.fp_img_empty, self.fp_img_empty, self.fp_img_empty, self.fp_img_empty]
     
     def compute_img2(self, *args):
@@ -156,9 +154,19 @@ class BlendingFrontend():
         fp_img2 = os.path.join(self.dp_out, f"img2_{get_time('second')}.jpg")
         img2 = Image.fromarray(self.lb.compute_latents2(return_image=True))
         img2.save(fp_img2)
+        self.recycle_img2 = True
         return [self.fp_img_empty, self.fp_img_empty, self.fp_img_empty, fp_img2]
         
     def compute_transition(self, *args):
+        
+        if not self.recycle_img1:
+            print("compute first image before transition")
+            return
+        if not self.recycle_img2:
+            print("compute last image before transition")
+            return
+        
+        
         list_ui_elem = args
         self.setup_lb(list_ui_elem)
         print("STARTING DIFFUSION!")
@@ -172,10 +180,11 @@ class BlendingFrontend():
         
         # Run Latent Blending
         imgs_transition = self.lb.run_transition(
-            recycle_img1=True, 
+            recycle_img1=self.recycle_img1, 
-            recycle_img2=True, 
+            recycle_img2=self.recycle_img2, 
             num_inference_steps=self.num_inference_steps, 
             depth_strength=self.depth_strength, 
+            t_compute_max_allowed=self.t_compute_max_allowed,
             fixed_seeds=fixed_seeds
             )
         print(f"Latent Blending pass finished. Resulted in {len(imgs_transition)} images")
@@ -222,9 +231,8 @@ class BlendingFrontend():
     
     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)
+        dp_out = os.path.join(self.dp_out, get_time('second'))
-        self.dict_multi_trans_include[self.current_timestamp] = True
+        self.lb.write_imgs_transition(dp_out)
-        
         self.lb.swap_forward()
         list_out = [self.list_fp_imgs_current[-1]]
         list_out.extend([self.fp_img_empty]*4)
@@ -232,18 +240,13 @@ class BlendingFrontend():
         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)
@@ -262,43 +265,6 @@ class BlendingFrontend():
         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)
@@ -389,6 +355,9 @@ if __name__ == "__main__":
         with gr.Row():
             vid_transition = gr.Video()
             
+        with gr.Row():
+            b_stackforward = gr.Button('multi-movie start next segment (move last image -> first image)')
+        
         # Collect all UI elemts in list to easily pass as inputs
         dict_ui_elem["prompt1"] = prompt1
         dict_ui_elem["negative_prompt"] = negative_prompt
@@ -430,4 +399,7 @@ if __name__ == "__main__":
                                     inputs=list_ui_elem,
                                     outputs=[img2, img3, img4, vid_transition])
         
+        b_stackforward.click(self.stack_forward, 
+                      inputs=[prompt2, seed2], 
+                      outputs=[img1, img2, img3, img4, img5, prompt1, seed1, prompt2])
     demo.launch(share=self.share, inbrowser=True, inline=False)