diff --git a/gradio_ui.py b/gradio_ui.py index dec7ea4..ebea227 100644 --- a/gradio_ui.py +++ b/gradio_ui.py @@ -59,6 +59,7 @@ class BlendingFrontend(): self.init_save_dir() self.save_empty_image() self.share = False + self.transition_can_be_computed = False self.depth_strength = 0.25 self.seed1 = 420 self.seed2 = 420 @@ -69,14 +70,12 @@ class BlendingFrontend(): self.prompt2 = "" self.negative_prompt = "" self.state_current = {} - self.branch1_influence = 0.3 - self.branch1_max_depth_influence = 0.6 - self.branch1_influence_decay = 0.3 - self.parental_influence = 0.1 - self.parental_max_depth_influence = 1.0 - self.parental_influence_decay = 1.0 - self.nmb_branches_final = 9 - self.nmb_imgs_show = 5 # don't change + self.branch1_crossfeed_power = self.lb.branch1_crossfeed_power + self.branch1_crossfeed_range = self.lb.branch1_crossfeed_range + self.branch1_crossfeed_decay = self.lb.branch1_crossfeed_decay + self.parental_crossfeed_power = self.lb.parental_crossfeed_power + self.parental_crossfeed_range = self.lb.parental_crossfeed_range + self.parental_crossfeed_power_decay = self.lb.parental_crossfeed_power_decay self.fps = 30 self.duration_video = 10 self.t_compute_max_allowed = 10 @@ -87,15 +86,14 @@ class BlendingFrontend(): self.fp_img1 = None self.fp_img2 = None self.multi_idx_current = -1 - self.multi_list_concat = [] self.list_imgs_shown_last = 5*[self.fp_img_empty] - self.nmb_trans_stack = 6 - + self.list_all_segments = [] + self.dp_session = "" def init_save_dir(self): load_dotenv(find_dotenv(), verbose=False) - self.dp_out = os.getenv("dp_out") + self.dp_out = os.getenv("DIR_OUT") if self.dp_out is None: self.dp_out = "" self.dp_imgs = os.path.join(self.dp_out, "imgs") @@ -104,7 +102,6 @@ class BlendingFrontend(): os.makedirs(self.dp_movies, exist_ok=True) - # make dummy image def save_empty_image(self): self.fp_img_empty = os.path.join(self.dp_imgs, 'empty.jpg') @@ -112,7 +109,11 @@ class BlendingFrontend(): def randomize_seed1(self): - seed = np.random.randint(0, 10000000) + # Dont randomize seed if we are in a multi concat mode. we don't want to change this one otherwise the movie breaks + if len(self.list_all_segments) > 0: + seed = self.seed1 + else: + seed = np.random.randint(0, 10000000) self.seed1 = int(seed) print(f"randomize_seed1: new seed = {self.seed1}") return seed @@ -141,12 +142,12 @@ class BlendingFrontend(): self.lb.seed1 = list_ui_elem[list_ui_keys.index('seed1')] #seed self.lb.seed2 = list_ui_elem[list_ui_keys.index('seed2')] - self.lb.branch1_influence = list_ui_elem[list_ui_keys.index('branch1_influence')] - self.lb.branch1_max_depth_influence = list_ui_elem[list_ui_keys.index('branch1_max_depth_influence')] - self.lb.branch1_influence_decay = list_ui_elem[list_ui_keys.index('branch1_influence_decay')] - self.lb.parental_influence = list_ui_elem[list_ui_keys.index('parental_influence')] - self.lb.parental_max_depth_influence = list_ui_elem[list_ui_keys.index('parental_max_depth_influence')] - self.lb.parental_influence_decay = list_ui_elem[list_ui_keys.index('parental_influence_decay')] + self.lb.branch1_crossfeed_power = list_ui_elem[list_ui_keys.index('branch1_crossfeed_power')] + self.lb.branch1_crossfeed_range = list_ui_elem[list_ui_keys.index('branch1_crossfeed_range')] + self.lb.branch1_crossfeed_decay = list_ui_elem[list_ui_keys.index('branch1_crossfeed_decay')] + self.lb.parental_crossfeed_power = list_ui_elem[list_ui_keys.index('parental_crossfeed_power')] + self.lb.parental_crossfeed_range = list_ui_elem[list_ui_keys.index('parental_crossfeed_range')] + self.lb.parental_crossfeed_power_decay = list_ui_elem[list_ui_keys.index('parental_crossfeed_power_decay')] self.num_inference_steps = list_ui_elem[list_ui_keys.index('num_inference_steps')] self.depth_strength = list_ui_elem[list_ui_keys.index('depth_strength')] @@ -162,27 +163,26 @@ class BlendingFrontend(): return [self.fp_img1, self.fp_img_empty, self.fp_img_empty, self.fp_img_empty, self.fp_img_empty] def compute_img2(self, *args): + if self.fp_img1 is None: # don't do anything + return [self.fp_img_empty, self.fp_img_empty, self.fp_img_empty, self.fp_img_empty] list_ui_elem = args self.setup_lb(list_ui_elem) self.fp_img2 = os.path.join(self.dp_imgs, f"img2_{get_time('second')}.jpg") img2 = Image.fromarray(self.lb.compute_latents2(return_image=True)) img2.save(self.fp_img2) self.recycle_img2 = True + self.transition_can_be_computed = True return [self.fp_img_empty, self.fp_img_empty, self.fp_img_empty, self.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 - + if not self.transition_can_be_computed: + list_return = [self.fp_img_empty, self.fp_img_empty, self.fp_img_empty, self.fp_img_empty] + return list_return list_ui_elem = args self.setup_lb(list_ui_elem) - print("STARTING DIFFUSION!") + print("STARTING TRANSITION...") 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] @@ -236,14 +236,21 @@ class BlendingFrontend(): def stack_forward(self, prompt2, seed2): # Save preview images, prompts and seeds into dictionary for stacking - # self.list_imgs_shown_last = self.get_multi_trans_imgs_preview(f"lowres_{self.current_timestamp}")[0:5] - timestamp_section = get_time('second') - self.lb.write_imgs_transition(os.path.join(self.dp_out, f"lowres_{timestamp_section}")) - self.lb.write_imgs_transition(os.path.join(self.dp_out, "lowres_current")) - shutil.copyfile(self.fp_movie, os.path.join(self.dp_out, f"lowres_{timestamp_section}", "movie.mp4")) + if len(self.list_all_segments) == 0: + timestamp_session = get_time('second') + self.dp_session = os.path.join(self.dp_out, f"session_{timestamp_session}") + os.makedirs(self.dp_session) + + self.transition_can_be_computed = False + + idx_segment = len(self.list_all_segments) + dp_segment = os.path.join(self.dp_session, f"segment_{str(idx_segment).zfill(3)}") + + self.list_all_segments.append(dp_segment) + self.lb.write_imgs_transition(dp_segment) + shutil.copyfile(self.fp_movie, os.path.join(dp_segment, "movie.mp4")) self.lb.swap_forward() - self.multi_append() fp_multi = self.multi_concat() list_out = [fp_multi] list_out.extend([self.fp_img2]) @@ -252,52 +259,19 @@ class BlendingFrontend(): list_out.append(gr.update(interactive=False, value=seed2)) list_out.append("") list_out.append(np.random.randint(0, 10000000)) - print(f"stack_forward: fp_multi {fp_multi}") return list_out - - def get_list_all_stacked(self): - list_all = os.listdir(os.path.join(self.dp_out)) - list_all = [l for l in list_all if l[:8]=="lowres_2"] - list_all.sort() - return list_all - def multi_append(self): - list_all = self.get_list_all_stacked() - dn = list_all[self.multi_idx_current] - self.multi_list_concat.append(dn) - list_short = [dn[7:] for dn in self.multi_list_concat] - str_out = "\n".join(list_short) - return str_out - - def multi_reset(self): - self.multi_list_concat = [] - str_out = "" - return str_out - def multi_concat(self): - # Make new output directory - dp_multi = os.path.join(self.dp_out, f"multi_{get_time('second')}") - os.makedirs(dp_multi, exist_ok=False) - - # Copy all low-res folders (prepending multi001_xxxx), however leave out the movie.mp4 - # also collect all movie.mp4 list_fp_movies = [] - for i, dn in enumerate(self.multi_list_concat): - dp_source = os.path.join(self.dp_out, dn) - dp_sequence = os.path.join(dp_multi, f"{str(i).zfill(3)}_{dn}") - os.makedirs(dp_sequence, exist_ok=False) - list_source = os.listdir(dp_source) - list_source = [l for l in list_source if not l.endswith(".mp4")] - for fn in list_source: - shutil.copyfile(os.path.join(dp_source, fn), os.path.join(dp_sequence, fn)) - list_fp_movies.append(os.path.join(dp_source, "movie.mp4")) - + for dp_segment in self.list_all_segments: + list_fp_movies.append(os.path.join(dp_segment, "movie.mp4")) + # Concatenate movies and save - fp_final = os.path.join(dp_multi, "movie.mp4") + fp_final = os.path.join(self.dp_session, "movie.mp4") concatenate_movies(fp_final, list_fp_movies) return fp_final @@ -312,36 +286,13 @@ class BlendingFrontend(): return state_dict -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_512-ema-pruned.ckpt" - self = BlendingFrontend(StableDiffusionHolder(fp_ckpt)) # Yes this is possible in python and yes it is an awesome trick - # self = BlendingFrontend(None) # Yes this is possible in python and yes it is an awesome trick - - dict_ui_elem = {} + bf = BlendingFrontend(StableDiffusionHolder(fp_ckpt)) + # self = BlendingFrontend(None) with gr.Blocks() as demo: with gr.Tab("Single Transition"): @@ -350,40 +301,40 @@ if __name__ == "__main__": prompt2 = gr.Textbox(label="prompt 2") with gr.Row(): - duration_compute = gr.Slider(5, 45, self.t_compute_max_allowed, step=1, label='compute budget for transition (seconds)', interactive=True) - duration_video = gr.Slider(0.1, 30, self.duration_video, step=0.1, label='result video duration (seconds)', interactive=True) - height = gr.Slider(256, 2048, self.height, step=128, label='height', interactive=True) - width = gr.Slider(256, 2048, self.width, step=128, label='width', interactive=True) + duration_compute = gr.Slider(5, 200, bf.t_compute_max_allowed, step=1, label='compute budget for transition (seconds)', interactive=True) + duration_video = gr.Slider(1, 100, bf.duration_video, step=0.1, label='result video duration (seconds)', interactive=True) + height = gr.Slider(256, 2048, bf.height, step=128, label='height', interactive=True) + width = gr.Slider(256, 2048, bf.width, step=128, label='width', interactive=True) with gr.Accordion("Advanced Settings (click to expand)", open=False): with gr.Accordion("Diffusion settings", open=True): with gr.Row(): - num_inference_steps = gr.Slider(5, 100, self.num_inference_steps, step=1, label='num_inference_steps', interactive=True) - guidance_scale = gr.Slider(1, 25, self.guidance_scale, step=0.1, label='guidance_scale', interactive=True) + num_inference_steps = gr.Slider(5, 100, bf.num_inference_steps, step=1, label='num_inference_steps', interactive=True) + guidance_scale = gr.Slider(1, 25, bf.guidance_scale, step=0.1, label='guidance_scale', interactive=True) negative_prompt = gr.Textbox(label="negative prompt") - with gr.Accordion("Seeds control", open=True): + with gr.Accordion("Seed control: adjust seeds for first and last images", open=True): with gr.Row(): b_newseed1 = gr.Button("randomize seed 1", variant='secondary') - seed1 = gr.Number(self.seed1, label="seed 1", interactive=True) - seed2 = gr.Number(self.seed2, label="seed 2", interactive=True) + seed1 = gr.Number(bf.seed1, label="seed 1", interactive=True) + seed2 = gr.Number(bf.seed2, label="seed 2", interactive=True) b_newseed2 = gr.Button("randomize seed 2", variant='secondary') - with gr.Accordion("Crossfeeding for last image", open=True): + with gr.Accordion("Last image crossfeeding.", open=True): with gr.Row(): - branch1_influence = gr.Slider(0.0, 1.0, self.branch1_influence, step=0.01, label='crossfeed power', interactive=True) - branch1_max_depth_influence = gr.Slider(0.0, 1.0, self.branch1_max_depth_influence, step=0.01, label='crossfeed range', interactive=True) - branch1_influence_decay = gr.Slider(0.0, 1.0, self.branch1_influence_decay, step=0.01, label='crossfeed decay', interactive=True) + branch1_crossfeed_power = gr.Slider(0.0, 1.0, bf.branch1_crossfeed_power, step=0.01, label='branch1 crossfeed power', interactive=True) + branch1_crossfeed_range = gr.Slider(0.0, 1.0, bf.branch1_crossfeed_range, step=0.01, label='branch1 crossfeed range', interactive=True) + branch1_crossfeed_decay = gr.Slider(0.0, 1.0, bf.branch1_crossfeed_decay, step=0.01, label='branch1 crossfeed decay', interactive=True) with gr.Accordion("Transition settings", open=True): with gr.Row(): - parental_influence = gr.Slider(0.0, 1.0, self.parental_influence, step=0.01, label='parental power', interactive=True) - parental_max_depth_influence = gr.Slider(0.0, 1.0, self.parental_max_depth_influence, step=0.01, label='parental range', interactive=True) - parental_influence_decay = gr.Slider(0.0, 1.0, self.parental_influence_decay, step=0.01, label='parental decay', interactive=True) + parental_crossfeed_power = gr.Slider(0.0, 1.0, bf.parental_crossfeed_power, step=0.01, label='parental crossfeed power', interactive=True) + parental_crossfeed_range = gr.Slider(0.0, 1.0, bf.parental_crossfeed_range, step=0.01, label='parental crossfeed range', interactive=True) + parental_crossfeed_power_decay = gr.Slider(0.0, 1.0, bf.parental_crossfeed_power_decay, step=0.01, label='parental crossfeed decay', interactive=True) with gr.Row(): - depth_strength = gr.Slider(0.01, 0.99, self.depth_strength, step=0.01, label='depth_strength', 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) + depth_strength = gr.Slider(0.01, 0.99, bf.depth_strength, step=0.01, label='depth_strength', interactive=True) + guidance_scale_mid_damper = gr.Slider(0.01, 2.0, bf.guidance_scale_mid_damper, step=0.01, label='guidance_scale_mid_damper', interactive=True) with gr.Row(): @@ -404,10 +355,11 @@ if __name__ == "__main__": with gr.Row(): # b_restart = gr.Button("RESTART EVERYTHING") - b_stackforward = gr.Button('multi-movie start next segment (move last image -> first image)', variant='primary') + b_stackforward = gr.Button('append last movie segment (left) to multi movie (right)', variant='primary') - # Collect all UI elemts in list to easily pass as inputs + # Collect all UI elemts in list to easily pass as inputs in gradio + dict_ui_elem = {} dict_ui_elem["prompt1"] = prompt1 dict_ui_elem["negative_prompt"] = negative_prompt dict_ui_elem["prompt2"] = prompt2 @@ -418,9 +370,9 @@ if __name__ == "__main__": dict_ui_elem["width"] = width dict_ui_elem["depth_strength"] = depth_strength - dict_ui_elem["branch1_influence"] = branch1_influence - dict_ui_elem["branch1_max_depth_influence"] = branch1_max_depth_influence - dict_ui_elem["branch1_influence_decay"] = branch1_influence_decay + dict_ui_elem["branch1_crossfeed_power"] = branch1_crossfeed_power + dict_ui_elem["branch1_crossfeed_range"] = branch1_crossfeed_range + dict_ui_elem["branch1_crossfeed_decay"] = branch1_crossfeed_decay dict_ui_elem["num_inference_steps"] = num_inference_steps dict_ui_elem["guidance_scale"] = guidance_scale @@ -428,9 +380,9 @@ if __name__ == "__main__": dict_ui_elem["seed1"] = seed1 dict_ui_elem["seed2"] = seed2 - dict_ui_elem["parental_max_depth_influence"] = parental_max_depth_influence - dict_ui_elem["parental_influence"] = parental_influence - dict_ui_elem["parental_influence_decay"] = parental_influence_decay + dict_ui_elem["parental_crossfeed_range"] = parental_crossfeed_range + dict_ui_elem["parental_crossfeed_power"] = parental_crossfeed_power + dict_ui_elem["parental_crossfeed_power_decay"] = parental_crossfeed_power_decay # Convert to list, as gradio doesn't seem to accept dicts list_ui_elem = [] @@ -438,21 +390,19 @@ if __name__ == "__main__": for k in dict_ui_elem.keys(): list_ui_elem.append(dict_ui_elem[k]) list_ui_keys.append(k) - self.list_ui_keys = list_ui_keys + bf.list_ui_keys = list_ui_keys - b_newseed1.click(self.randomize_seed1, outputs=seed1) - b_newseed2.click(self.randomize_seed2, outputs=seed2) - b_compute1.click(self.compute_img1, inputs=list_ui_elem, outputs=[img1, img2, img3, img4, img5]) - b_compute2.click(self.compute_img2, inputs=list_ui_elem, outputs=[img2, img3, img4, img5]) - b_compute_transition.click(self.compute_transition, + b_newseed1.click(bf.randomize_seed1, outputs=seed1) + b_newseed2.click(bf.randomize_seed2, outputs=seed2) + b_compute1.click(bf.compute_img1, inputs=list_ui_elem, outputs=[img1, img2, img3, img4, img5]) + b_compute2.click(bf.compute_img2, inputs=list_ui_elem, outputs=[img2, img3, img4, img5]) + b_compute_transition.click(bf.compute_transition, inputs=list_ui_elem, outputs=[img2, img3, img4, vid_single]) - b_stackforward.click(self.stack_forward, + b_stackforward.click(bf.stack_forward, inputs=[prompt2, seed2], outputs=[vid_multi, img1, img2, img3, img4, img5, prompt1, seed1, prompt2]) - # b_restart.click(self.multi_reset) - - demo.launch(share=self.share, inbrowser=True, inline=False) + demo.launch(share=bf.share, inbrowser=True, inline=False) diff --git a/latent_blending.py b/latent_blending.py index 4a5fbf1..3537d4d 100644 --- a/latent_blending.py +++ b/latent_blending.py @@ -109,13 +109,13 @@ class LatentBlending(): self.list_nmb_branches = None # Mixing parameters - self.branch1_influence = 0.0 - self.branch1_max_depth_influence = 0.65 - self.branch1_influence_decay = 0.8 + self.branch1_crossfeed_power = 0.1 + self.branch1_crossfeed_range = 0.6 + self.branch1_crossfeed_decay = 0.8 - self.parental_influence = 0.0 - self.parental_max_depth_influence = 1.0 - self.parental_influence_decay = 1.0 + self.parental_crossfeed_power = 0.1 + self.parental_crossfeed_range = 0.8 + self.parental_crossfeed_power_decay = 0.8 self.branch1_insertion_completed = False self.set_guidance_scale(guidance_scale) @@ -335,10 +335,10 @@ class LatentBlending(): list_conditionings = self.get_mixed_conditioning(1) latents_start = self.get_noise(self.seed2) # Influence from branch1 - if self.branch1_influence > 0.0: + if self.branch1_crossfeed_power > 0.0: # Set up the mixing_coeffs - idx_mixing_stop = int(round(self.num_inference_steps*self.branch1_max_depth_influence)) - mixing_coeffs = list(np.linspace(self.branch1_influence, self.branch1_influence*self.branch1_influence_decay, idx_mixing_stop)) + idx_mixing_stop = int(round(self.num_inference_steps*self.branch1_crossfeed_range)) + mixing_coeffs = list(np.linspace(self.branch1_crossfeed_power, self.branch1_crossfeed_power*self.branch1_crossfeed_decay, idx_mixing_stop)) mixing_coeffs.extend((self.num_inference_steps-idx_mixing_stop)*[0]) list_latents_mixing = self.tree_latents[0] list_latents2 = self.run_diffusion( @@ -385,11 +385,11 @@ class LatentBlending(): latents_parental = interpolate_spherical(latents_p1, latents_p2, fract_mixing_parental) list_latents_parental_mix.append(latents_parental) - idx_mixing_stop = int(round(self.num_inference_steps*self.parental_max_depth_influence)) - mixing_coeffs = idx_injection*[self.parental_influence] + idx_mixing_stop = int(round(self.num_inference_steps*self.parental_crossfeed_range)) + mixing_coeffs = idx_injection*[self.parental_crossfeed_power] nmb_mixing = idx_mixing_stop - idx_injection if nmb_mixing > 0: - mixing_coeffs.extend(list(np.linspace(self.parental_influence, self.parental_influence*self.parental_influence_decay, nmb_mixing))) + mixing_coeffs.extend(list(np.linspace(self.parental_crossfeed_power, self.parental_crossfeed_power*self.parental_crossfeed_power_decay, nmb_mixing))) mixing_coeffs.extend((self.num_inference_steps-len(mixing_coeffs))*[0]) latents_start = list_latents_parental_mix[idx_injection-1] @@ -793,8 +793,8 @@ class LatentBlending(): grab_vars = ['prompt1', 'prompt2', 'seed1', 'seed2', 'height', 'width', 'num_inference_steps', 'depth_strength', 'guidance_scale', 'guidance_scale_mid_damper', 'mid_compression_scaler', 'negative_prompt', - 'branch1_influence', 'branch1_max_depth_influence', 'branch1_influence_decay' - 'parental_influence', 'parental_max_depth_influence', 'parental_influence_decay'] + 'branch1_crossfeed_power', 'branch1_crossfeed_range', 'branch1_crossfeed_decay' + 'parental_crossfeed_power', 'parental_crossfeed_range', 'parental_crossfeed_power_decay'] for v in grab_vars: if hasattr(self, v): if v == 'seed1' or v == 'seed2': @@ -1167,25 +1167,25 @@ if __name__ == "__main__": self.set_prompt2(prompt2) # Run latent blending - self.branch1_influence = 0.3 - self.branch1_max_depth_influence = 0.4 + self.branch1_crossfeed_power = 0.3 + self.branch1_crossfeed_range = 0.4 # self.run_transition(depth_strength=depth_strength, fixed_seeds=fixed_seeds) self.seed1=21312 img1 =self.compute_latents1(True) #% self.seed2=1234121 - self.branch1_influence = 0.7 - self.branch1_max_depth_influence = 0.3 - self.branch1_influence_decay = 0.3 + self.branch1_crossfeed_power = 0.7 + self.branch1_crossfeed_range = 0.3 + self.branch1_crossfeed_decay = 0.3 img2 =self.compute_latents2(True) # Image.fromarray(np.concatenate((img1, img2), axis=1)) #%% t0 = time.time() self.t_compute_max_allowed = 30 - self.parental_max_depth_influence = 1.0 - self.parental_influence = 0.0 - self.parental_influence_decay = 1.0 + self.parental_crossfeed_range = 1.0 + self.parental_crossfeed_power = 0.0 + self.parental_crossfeed_power_decay = 1.0 imgs_transition = self.run_transition(recycle_img1=True, recycle_img2=True) t1 = time.time() print(f"took: {t1-t0}s") \ No newline at end of file