multi transition movies
This commit is contained in:
Johannes Stelzer
parent
20a80a5d1f
commit
da1877ce37
84
gradio_ui.py
84
gradio_ui.py
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@ -56,9 +56,7 @@ class BlendingFrontend():
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self.prompt1 = ""
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self.prompt2 = ""
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self.negative_prompt = ""
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self.list_settings = []
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self.state_current = {}
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self.showing_current = True
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self.branch1_influence = 0.3
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self.branch1_max_depth_influence = 0.6
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self.branch1_influence_decay = 0.3
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@ -70,12 +68,10 @@ class BlendingFrontend():
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self.fps = 30
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self.duration_video = 10
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self.t_compute_max_allowed = 10
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self.dict_multi_trans = {}
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self.dict_multi_trans_include = {}
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self.multi_trans_currently_shown = []
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self.list_fp_imgs_current = []
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self.current_timestamp = None
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self.nmb_trans_stack = 8
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self.recycle_img1 = False
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self.recycle_img2 = False
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if not self.use_debug:
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self.lb.sdh.num_inference_steps = self.num_inference_steps
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@ -125,7 +121,7 @@ class BlendingFrontend():
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self.lb.set_negative_prompt(list_ui_elem[list_ui_keys.index('negative_prompt')])
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self.lb.guidance_scale = list_ui_elem[list_ui_keys.index('guidance_scale')]
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self.lb.guidance_scale_mid_damper = list_ui_elem[list_ui_keys.index('guidance_scale_mid_damper')]
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self.lb.t_compute_max_allowed = list_ui_elem[list_ui_keys.index('duration_compute')]
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self.t_compute_max_allowed = list_ui_elem[list_ui_keys.index('duration_compute')]
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self.lb.num_inference_steps = list_ui_elem[list_ui_keys.index('num_inference_steps')]
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self.lb.sdh.num_inference_steps = list_ui_elem[list_ui_keys.index('num_inference_steps')]
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self.duration_video = list_ui_elem[list_ui_keys.index('duration_video')]
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@ -148,6 +144,8 @@ class BlendingFrontend():
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img1 = Image.fromarray(self.lb.compute_latents1(return_image=True))
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img1.save(fp_img1)
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self.save_empty_image()
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self.recycle_img1 = True
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self.recycle_img2 = False
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return [fp_img1, self.fp_img_empty, self.fp_img_empty, self.fp_img_empty, self.fp_img_empty]
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def compute_img2(self, *args):
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@ -156,9 +154,19 @@ class BlendingFrontend():
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fp_img2 = os.path.join(self.dp_out, f"img2_{get_time('second')}.jpg")
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img2 = Image.fromarray(self.lb.compute_latents2(return_image=True))
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img2.save(fp_img2)
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self.recycle_img2 = True
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return [self.fp_img_empty, self.fp_img_empty, self.fp_img_empty, fp_img2]
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def compute_transition(self, *args):
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if not self.recycle_img1:
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print("compute first image before transition")
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return
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if not self.recycle_img2:
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print("compute last image before transition")
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return
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list_ui_elem = args
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self.setup_lb(list_ui_elem)
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print("STARTING DIFFUSION!")
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@ -172,10 +180,11 @@ class BlendingFrontend():
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# Run Latent Blending
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imgs_transition = self.lb.run_transition(
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recycle_img1=True,
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recycle_img2=True,
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recycle_img1=self.recycle_img1,
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recycle_img2=self.recycle_img2,
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num_inference_steps=self.num_inference_steps,
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depth_strength=self.depth_strength,
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t_compute_max_allowed=self.t_compute_max_allowed,
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fixed_seeds=fixed_seeds
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)
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print(f"Latent Blending pass finished. Resulted in {len(imgs_transition)} images")
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@ -222,9 +231,8 @@ class BlendingFrontend():
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def stack_forward(self, prompt2, seed2):
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# Save preview images, prompts and seeds into dictionary for stacking
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self.dict_multi_trans[self.current_timestamp] = generate_list_output(self.prompt1, self.prompt2, self.seed1, self.seed2, self.list_fp_imgs_current)
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self.dict_multi_trans_include[self.current_timestamp] = True
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dp_out = os.path.join(self.dp_out, get_time('second'))
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self.lb.write_imgs_transition(dp_out)
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self.lb.swap_forward()
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list_out = [self.list_fp_imgs_current[-1]]
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list_out.extend([self.fp_img_empty]*4)
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@ -232,18 +240,13 @@ class BlendingFrontend():
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list_out.append(seed2)
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list_out.append("")
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list_out.append(np.random.randint(0, 10000000))
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list_out_multi_tab = self.update_trans_stacks()
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list_out.extend(list_out_multi_tab)
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# self.nmb_trans_stack = len(self.dict_multi_trans_include)
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return list_out
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def stack_movie(self):
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# collect all that are in...
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list_fp_movies = []
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for timestamp in self.multi_trans_currently_shown:
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if timestamp is not None:
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list_fp_movies.append(self.get_fp_movie(timestamp))
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fp_stacked = self.get_fp_movie(get_time('second'), True)
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@ -262,43 +265,6 @@ class BlendingFrontend():
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return state_dict
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def update_trans_stacks(self):
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print("Updating transition stack...")
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self.multi_trans_currently_shown = []
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list_output = []
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# Figure out which transitions should be shown
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for timestamp in self.dict_multi_trans_include.keys():
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if len(self.multi_trans_currently_shown) >= self.nmb_trans_stack:
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continue
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if self.dict_multi_trans_include[timestamp]:
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last_timestamp_vals = self.dict_multi_trans[timestamp]
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list_output.extend(self.dict_multi_trans[timestamp])
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self.multi_trans_currently_shown.append(timestamp)
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print(f"including timestamp: {timestamp}")
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# Fill with empty images if below nmb_trans_stack
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nmb_empty_missing = self.nmb_trans_stack - len(self.multi_trans_currently_shown)
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for i in range(nmb_empty_missing):
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list_output.extend([gr.update(visible=False)]*len(last_timestamp_vals))
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self.multi_trans_currently_shown.append(None)
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return list_output
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def remove_trans(self, idx_row):
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idx_row = int(idx_row)
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# do removal...
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if idx_row < len(self.multi_trans_currently_shown):
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timestamp = self.multi_trans_currently_shown[idx_row]
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if timestamp in self.dict_multi_trans_include.keys():
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self.dict_multi_trans_include[timestamp] = False
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print(f"remove_trans called: {timestamp}")
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else:
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print(f"remove_trans called: idx_row too large {idx_row}")
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return self.update_trans_stacks()
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def get_img_rand():
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return (255*np.random.rand(self.height,self.width,3)).astype(np.uint8)
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@ -389,6 +355,9 @@ if __name__ == "__main__":
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with gr.Row():
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vid_transition = gr.Video()
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with gr.Row():
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b_stackforward = gr.Button('multi-movie start next segment (move last image -> first image)')
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# Collect all UI elemts in list to easily pass as inputs
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dict_ui_elem["prompt1"] = prompt1
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dict_ui_elem["negative_prompt"] = negative_prompt
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@ -430,4 +399,7 @@ if __name__ == "__main__":
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inputs=list_ui_elem,
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outputs=[img2, img3, img4, vid_transition])
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b_stackforward.click(self.stack_forward,
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inputs=[prompt2, seed2],
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outputs=[img1, img2, img3, img4, img5, prompt1, seed1, prompt2])
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demo.launch(share=self.share, inbrowser=True, inline=False)
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