multi user support for gradio (huggingface server)
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cc8baf6c72
commit
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126
gradio_ui.py
126
gradio_ui.py
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@ -33,7 +33,8 @@ import gradio as gr
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import copy
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import copy
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from dotenv import find_dotenv, load_dotenv
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from dotenv import find_dotenv, load_dotenv
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import shutil
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import shutil
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import random
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import time
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#%%
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#%%
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@ -54,7 +55,7 @@ class BlendingFrontend():
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self.init_save_dir()
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self.init_save_dir()
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self.save_empty_image()
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self.save_empty_image()
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self.share = True
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self.share = False
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self.transition_can_be_computed = False
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self.transition_can_be_computed = False
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self.depth_strength = 0.25
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self.depth_strength = 0.25
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self.seed1 = 420
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self.seed1 = 420
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@ -79,12 +80,12 @@ class BlendingFrontend():
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self.current_timestamp = None
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self.current_timestamp = None
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self.recycle_img1 = False
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self.recycle_img1 = False
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self.recycle_img2 = False
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self.recycle_img2 = False
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self.fp_img1 = None
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self.fp_img2 = None
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self.multi_idx_current = -1
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self.multi_idx_current = -1
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self.list_imgs_shown_last = 5*[self.fp_img_empty]
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self.list_imgs_shown_last = 5*[self.fp_img_empty]
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self.list_all_segments = []
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self.list_all_segments = []
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self.dp_session = ""
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self.dp_session = ""
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self.user_id = None
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self.block_transition = False
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def init_save_dir(self):
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def init_save_dir(self):
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@ -106,9 +107,6 @@ class BlendingFrontend():
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def randomize_seed1(self):
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def randomize_seed1(self):
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# Dont randomize seed if we are in a multi concat mode. we don't want to change this one otherwise the movie breaks
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# Dont randomize seed if we are in a multi concat mode. we don't want to change this one otherwise the movie breaks
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if len(self.list_all_segments) > 0:
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seed = self.seed1
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else:
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seed = np.random.randint(0, 10000000)
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seed = np.random.randint(0, 10000000)
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self.seed1 = int(seed)
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self.seed1 = int(seed)
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print(f"randomize_seed1: new seed = {self.seed1}")
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print(f"randomize_seed1: new seed = {self.seed1}")
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@ -147,47 +145,80 @@ class BlendingFrontend():
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self.num_inference_steps = list_ui_elem[list_ui_keys.index('num_inference_steps')]
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self.num_inference_steps = list_ui_elem[list_ui_keys.index('num_inference_steps')]
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self.depth_strength = list_ui_elem[list_ui_keys.index('depth_strength')]
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self.depth_strength = list_ui_elem[list_ui_keys.index('depth_strength')]
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if len(list_ui_elem[list_ui_keys.index('user_id')]) > 1:
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self.user_id = list_ui_elem[list_ui_keys.index('user_id')]
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else:
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# generate new user id
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self.user_id = ''.join((random.choice('ABCDEFGHIJKLMNOPQRSTUVWXYZ') for i in range(8)))
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print(f"made new user_id: {self.user_id}")
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def save_latents(self, fp_latents, list_latents):
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list_latents_cpu = [l.cpu().numpy() for l in list_latents]
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np.save(fp_latents, list_latents_cpu)
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def load_latents(self, fp_latents):
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list_latents_cpu = np.load(fp_latents)
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list_latents = [torch.from_numpy(l).to(self.lb.device) for l in list_latents_cpu]
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return list_latents
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def compute_img1(self, *args):
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def compute_img1(self, *args):
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list_ui_elem = args
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list_ui_elem = args
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self.setup_lb(list_ui_elem)
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self.setup_lb(list_ui_elem)
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self.fp_img1 = os.path.join(self.dp_imgs, f"img1_{get_time('second')}.jpg")
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fp_img1 = os.path.join(self.dp_imgs, f"img1_{self.user_id}")
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img1 = Image.fromarray(self.lb.compute_latents1(return_image=True))
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img1 = Image.fromarray(self.lb.compute_latents1(return_image=True))
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img1.save(self.fp_img1)
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img1.save(fp_img1+".jpg")
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self.save_latents(fp_img1+".npy", self.lb.tree_latents[0])
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self.recycle_img1 = True
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self.recycle_img1 = True
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self.recycle_img2 = False
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self.recycle_img2 = False
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return [self.fp_img1, self.fp_img_empty, self.fp_img_empty, self.fp_img_empty, self.fp_img_empty]
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# fixme save seeds. change filenames?
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return [fp_img1+".jpg", self.fp_img_empty, self.fp_img_empty, self.fp_img_empty, self.fp_img_empty, self.user_id]
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def compute_img2(self, *args):
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def compute_img2(self, *args):
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if self.fp_img1 is None: # don't do anything
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if not os.path.isfile(os.path.join(self.dp_imgs, f"img1_{self.user_id}.jpg")): # don't do anything
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return [self.fp_img_empty, self.fp_img_empty, self.fp_img_empty, self.fp_img_empty]
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return [self.fp_img_empty, self.fp_img_empty, self.fp_img_empty, self.fp_img_empty, self.user_id]
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list_ui_elem = args
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list_ui_elem = args
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self.setup_lb(list_ui_elem)
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self.setup_lb(list_ui_elem)
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self.fp_img2 = os.path.join(self.dp_imgs, f"img2_{get_time('second')}.jpg")
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self.lb.tree_latents[0] = self.load_latents(os.path.join(self.dp_imgs, f"img1_{self.user_id}.npy"))
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fp_img2 = os.path.join(self.dp_imgs, f"img2_{self.user_id}")
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img2 = Image.fromarray(self.lb.compute_latents2(return_image=True))
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img2 = Image.fromarray(self.lb.compute_latents2(return_image=True))
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img2.save(self.fp_img2)
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img2.save(fp_img2+'.jpg')
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self.save_latents(fp_img2+".npy", self.lb.tree_latents[-1])
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self.recycle_img2 = True
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self.recycle_img2 = True
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self.transition_can_be_computed = True
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self.transition_can_be_computed = True
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return [self.fp_img_empty, self.fp_img_empty, self.fp_img_empty, self.fp_img2]
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# fixme save seeds. change filenames?
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return [self.fp_img_empty, self.fp_img_empty, self.fp_img_empty, fp_img2+".jpg", self.user_id]
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def compute_transition(self, *args):
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def compute_transition(self, *args):
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if not self.transition_can_be_computed:
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if not self.transition_can_be_computed:
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list_return = [self.fp_img_empty, self.fp_img_empty, self.fp_img_empty, self.fp_img_empty]
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list_return = [self.fp_img_empty, self.fp_img_empty, self.fp_img_empty, self.fp_img_empty, self.user_id]
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return list_return
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return list_return
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list_ui_elem = args
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list_ui_elem = args
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self.setup_lb(list_ui_elem)
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self.setup_lb(list_ui_elem)
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print("STARTING TRANSITION...")
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print("STARTING TRANSITION...")
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if self.use_debug:
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list_imgs = [(255*np.random.rand(self.height,self.width,3)).astype(np.uint8) for l in range(5)]
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list_imgs = [Image.fromarray(l) for l in list_imgs]
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print("DONE! SENDING BACK RESULTS")
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return list_imgs
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fixed_seeds = [self.seed1, self.seed2]
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fixed_seeds = [self.seed1, self.seed2]
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# Run Latent Blending
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# Run Latent Blending
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# Check if another user is blocking this... otherwise everything will become mixed.
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# t_now = time.time()
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# if self.block_transition:
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# while True:
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# time.sleep(1)
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# if not self.block_transition:
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# break
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# if time.time() - t_now > 1000:
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# return
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self.block_transition = True
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# Inject loaded latents (other user interference)
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self.lb.tree_latents[0] = self.load_latents(os.path.join(self.dp_imgs, f"img1_{self.user_id}.npy"))
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self.lb.tree_latents[-1] = self.load_latents(os.path.join(self.dp_imgs, f"img2_{self.user_id}.npy"))
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imgs_transition = self.lb.run_transition(
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imgs_transition = self.lb.run_transition(
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recycle_img1=self.recycle_img1,
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recycle_img1=self.recycle_img1,
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recycle_img2=self.recycle_img2,
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recycle_img2=self.recycle_img2,
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@ -211,12 +242,12 @@ class BlendingFrontend():
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fp_img = os.path.join(self.dp_imgs, f"img_preview_{i}_{self.current_timestamp}.jpg")
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fp_img = os.path.join(self.dp_imgs, f"img_preview_{i}_{self.current_timestamp}.jpg")
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list_imgs_preview[i].save(fp_img)
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list_imgs_preview[i].save(fp_img)
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self.list_fp_imgs_current.append(fp_img)
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self.list_fp_imgs_current.append(fp_img)
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self.block_transition = False
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# Insert cheap frames for the movie
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# Insert cheap frames for the movie
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imgs_transition_ext = add_frames_linear_interp(imgs_transition, self.duration_video, self.fps)
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imgs_transition_ext = add_frames_linear_interp(imgs_transition, self.duration_video, self.fps)
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# Save as movie
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# Save as movie
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self.fp_movie = os.path.join(self.dp_movies, f"movie_{self.current_timestamp}.mp4")
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self.fp_movie = self.get_fp_video_last()
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if os.path.isfile(self.fp_movie):
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if os.path.isfile(self.fp_movie):
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os.remove(self.fp_movie)
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os.remove(self.fp_movie)
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ms = MovieSaver(self.fp_movie, fps=self.fps)
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ms = MovieSaver(self.fp_movie, fps=self.fps)
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@ -244,12 +275,17 @@ class BlendingFrontend():
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self.list_all_segments.append(dp_segment)
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self.list_all_segments.append(dp_segment)
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self.lb.write_imgs_transition(dp_segment)
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self.lb.write_imgs_transition(dp_segment)
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shutil.copyfile(self.fp_movie, os.path.join(dp_segment, "movie.mp4"))
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fp_movie_last = self.get_fp_video_last()
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fp_movie_next = self.get_fp_video_next()
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shutil.copyfile(fp_movie_last, fp_movie_next)
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self.lb.swap_forward()
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self.lb.swap_forward()
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fp_multi = self.multi_concat()
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fp_multi = self.multi_concat()
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list_out = [fp_multi]
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list_out = [fp_multi]
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list_out.extend([self.fp_img2])
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list_out.extend([os.path.join(self.dp_imgs, f"img2_{self.user_id}.jpg")])
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list_out.extend([self.fp_img_empty]*4)
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list_out.extend([self.fp_img_empty]*4)
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list_out.append(gr.update(interactive=False, value=prompt2))
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list_out.append(gr.update(interactive=False, value=prompt2))
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list_out.append(gr.update(interactive=False, value=seed2))
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list_out.append(gr.update(interactive=False, value=seed2))
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@ -260,15 +296,36 @@ class BlendingFrontend():
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def multi_concat(self):
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def multi_concat(self):
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list_fp_movies = []
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list_fp_movies = self.get_fp_video_all()
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for dp_segment in self.list_all_segments:
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list_fp_movies.append(os.path.join(dp_segment, "movie.mp4"))
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# Concatenate movies and save
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# Concatenate movies and save
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fp_final = os.path.join(self.dp_session, "movie.mp4")
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fp_final = os.path.join(self.dp_session, f"concat_{self.user_id}.mp4")
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concatenate_movies(fp_final, list_fp_movies)
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concatenate_movies(fp_final, list_fp_movies)
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return fp_final
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return fp_final
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def get_fp_video_all(self):
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list_all = os.listdir(self.dp_movies)
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str_beg = f"movie_{self.user_id}_"
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list_user = [l for l in list_all if str_beg in l]
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list_user.sort()
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list_user = [os.path.join(self.dp_movies, l) for l in list_user]
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return list_user
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def get_fp_video_next(self):
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list_videos = self.get_fp_video_all()
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if len(list_videos) == 0:
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idx_next = 0
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else:
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idx_next = len(list_videos)
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fp_video_next = os.path.join(self.dp_movies, f"movie_{self.user_id}_{str(idx_next).zfill(3)}.mp4")
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return fp_video_next
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def get_fp_video_last(self):
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fp_video_last = os.path.join(self.dp_movies, f"last_{self.user_id}.mp4")
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return fp_video_last
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def get_state_dict(self):
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def get_state_dict(self):
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state_dict = {}
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state_dict = {}
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grab_vars = ['prompt1', 'prompt2', 'seed1', 'seed2', 'height', 'width',
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grab_vars = ['prompt1', 'prompt2', 'seed1', 'seed2', 'height', 'width',
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"""
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"""
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)
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)
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with gr.Row():
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user_id = gr.Textbox(label="user id", interactive=False)
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# Collect all UI elemts in list to easily pass as inputs in gradio
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# Collect all UI elemts in list to easily pass as inputs in gradio
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dict_ui_elem = {}
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dict_ui_elem = {}
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dict_ui_elem["parental_crossfeed_range"] = parental_crossfeed_range
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dict_ui_elem["parental_crossfeed_range"] = parental_crossfeed_range
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dict_ui_elem["parental_crossfeed_power"] = parental_crossfeed_power
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dict_ui_elem["parental_crossfeed_power"] = parental_crossfeed_power
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dict_ui_elem["parental_crossfeed_power_decay"] = parental_crossfeed_power_decay
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dict_ui_elem["parental_crossfeed_power_decay"] = parental_crossfeed_power_decay
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dict_ui_elem["user_id"] = user_id
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# Convert to list, as gradio doesn't seem to accept dicts
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# Convert to list, as gradio doesn't seem to accept dicts
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list_ui_elem = []
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list_ui_elem = []
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b_newseed1.click(bf.randomize_seed1, outputs=seed1)
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b_newseed1.click(bf.randomize_seed1, outputs=seed1)
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b_newseed2.click(bf.randomize_seed2, outputs=seed2)
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b_newseed2.click(bf.randomize_seed2, outputs=seed2)
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b_compute1.click(bf.compute_img1, inputs=list_ui_elem, outputs=[img1, img2, img3, img4, img5])
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b_compute1.click(bf.compute_img1, inputs=list_ui_elem, outputs=[img1, img2, img3, img4, img5, user_id])
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b_compute2.click(bf.compute_img2, inputs=list_ui_elem, outputs=[img2, img3, img4, img5])
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b_compute2.click(bf.compute_img2, inputs=list_ui_elem, outputs=[img2, img3, img4, img5, user_id])
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b_compute_transition.click(bf.compute_transition,
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b_compute_transition.click(bf.compute_transition,
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inputs=list_ui_elem,
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inputs=list_ui_elem,
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outputs=[img2, img3, img4, vid_single])
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outputs=[img2, img3, img4, vid_single])
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