Spaces:
Build error
Build error
Update app.py
Browse files
app.py
CHANGED
|
@@ -1,12 +1,12 @@
|
|
| 1 |
import torch
|
| 2 |
-
|
| 3 |
# General
|
| 4 |
import os
|
| 5 |
from os.path import join as opj
|
| 6 |
import argparse
|
| 7 |
import datetime
|
| 8 |
from pathlib import Path
|
| 9 |
-
|
| 10 |
import gradio as gr
|
| 11 |
import tempfile
|
| 12 |
import yaml
|
|
@@ -59,7 +59,7 @@ msxl_model = init_v2v_model(cfg_v2v, devices[3])
|
|
| 59 |
# -------------------------
|
| 60 |
# ----- Functionality -----
|
| 61 |
# -------------------------
|
| 62 |
-
|
| 63 |
def generate(prompt, num_frames, image, model_name_stage1, model_name_stage2, seed, t, image_guidance, where_to_log=result_fol):
|
| 64 |
now = datetime.datetime.now()
|
| 65 |
name = prompt[:100].replace(" ", "_") + "_" + str(now.time()).replace(":", "_").replace(".", "_")
|
|
@@ -89,7 +89,7 @@ def generate(prompt, num_frames, image, model_name_stage1, model_name_stage2, se
|
|
| 89 |
video_path = opj(where_to_log, name+".mp4")
|
| 90 |
return video_path
|
| 91 |
|
| 92 |
-
|
| 93 |
def enhance(prompt, input_to_enhance, num_frames=None, image=None, model_name_stage1=None, model_name_stage2=None, seed=33, t=50, image_guidance=9.5, result_fol=result_fol):
|
| 94 |
if input_to_enhance is None:
|
| 95 |
input_to_enhance = generate(prompt, num_frames, image, model_name_stage1, model_name_stage2, seed, t, image_guidance)
|
|
@@ -105,26 +105,27 @@ def change_visibility(value):
|
|
| 105 |
return gr.Image(label='Image Prompt (first select Image-to-Video model from advanced options to enable image upload)', show_label=True, scale=1, show_download_button=False, interactive=False, value=None)
|
| 106 |
|
| 107 |
|
|
|
|
| 108 |
examples_1 = [
|
| 109 |
["Experience the dance of jellyfish: float through mesmerizing swarms of jellyfish, pulsating with otherworldly grace and beauty.",
|
| 110 |
-
|
| 111 |
["People dancing in room filled with fog and colorful lights.",
|
| 112 |
-
|
| 113 |
["Discover the secret language of bees: delve into the complex communication system that allows bees to coordinate their actions and navigate the world.",
|
| 114 |
-
|
| 115 |
["sunset, orange sky, warm lighting, fishing boats, ocean waves seagulls, rippling water, wharf, silhouette, serene atmosphere, dusk, evening glow, coastal landscape, seaside scenery.",
|
| 116 |
-
|
| 117 |
["Dive into the depths of the ocean: explore vibrant coral reefs, mysterious underwater caves, and the mesmerizing creatures that call the sea home.",
|
| 118 |
-
|
| 119 |
["Ants, beetles and centipede nest.",
|
| 120 |
-
|
| 121 |
]
|
| 122 |
|
| 123 |
examples_2 = [
|
| 124 |
["Fishes swimming in ocean camera moving, cinematic.",
|
| 125 |
-
|
| 126 |
["A squirrel on a table full of big nuts.",
|
| 127 |
-
|
| 128 |
]
|
| 129 |
|
| 130 |
# --------------------------
|
|
@@ -215,6 +216,8 @@ with gr.Blocks() as demo:
|
|
| 215 |
|
| 216 |
inputs_v2v = [prompt_stage1, video_stage1, num_frames, image_stage1, model_name_stage1, model_name_stage2, seed, t, image_guidance]
|
| 217 |
|
|
|
|
|
|
|
| 218 |
gr.HTML("""
|
| 219 |
<h2>
|
| 220 |
You can check the inference time for different number of frames
|
|
@@ -225,21 +228,21 @@ with gr.Blocks() as demo:
|
|
| 225 |
""")
|
| 226 |
|
| 227 |
gr.Examples(examples=examples_1,
|
| 228 |
-
inputs=
|
| 229 |
-
|
| 230 |
-
|
| 231 |
-
|
| 232 |
-
|
| 233 |
)
|
| 234 |
|
| 235 |
gr.Examples(examples=examples_2,
|
| 236 |
-
inputs=
|
| 237 |
-
|
| 238 |
-
|
| 239 |
-
|
| 240 |
-
|
| 241 |
-
|
| 242 |
-
|
| 243 |
)
|
| 244 |
|
| 245 |
run_button_stage2.click(fn=enhance, inputs=inputs_v2v, outputs=video_stage2,)
|
|
|
|
| 1 |
import torch
|
| 2 |
+
torch.jit.script = lambda f: f
|
| 3 |
# General
|
| 4 |
import os
|
| 5 |
from os.path import join as opj
|
| 6 |
import argparse
|
| 7 |
import datetime
|
| 8 |
from pathlib import Path
|
| 9 |
+
import spaces
|
| 10 |
import gradio as gr
|
| 11 |
import tempfile
|
| 12 |
import yaml
|
|
|
|
| 59 |
# -------------------------
|
| 60 |
# ----- Functionality -----
|
| 61 |
# -------------------------
|
| 62 |
+
@spaces.GPU(duration=120)
|
| 63 |
def generate(prompt, num_frames, image, model_name_stage1, model_name_stage2, seed, t, image_guidance, where_to_log=result_fol):
|
| 64 |
now = datetime.datetime.now()
|
| 65 |
name = prompt[:100].replace(" ", "_") + "_" + str(now.time()).replace(":", "_").replace(".", "_")
|
|
|
|
| 89 |
video_path = opj(where_to_log, name+".mp4")
|
| 90 |
return video_path
|
| 91 |
|
| 92 |
+
@spaces.GPU(duration=400)
|
| 93 |
def enhance(prompt, input_to_enhance, num_frames=None, image=None, model_name_stage1=None, model_name_stage2=None, seed=33, t=50, image_guidance=9.5, result_fol=result_fol):
|
| 94 |
if input_to_enhance is None:
|
| 95 |
input_to_enhance = generate(prompt, num_frames, image, model_name_stage1, model_name_stage2, seed, t, image_guidance)
|
|
|
|
| 105 |
return gr.Image(label='Image Prompt (first select Image-to-Video model from advanced options to enable image upload)', show_label=True, scale=1, show_download_button=False, interactive=False, value=None)
|
| 106 |
|
| 107 |
|
| 108 |
+
# [prompt_stage1, video_stage2, num_frames, image_stage1, model_name_stage1, seed, t, image_guidance]
|
| 109 |
examples_1 = [
|
| 110 |
["Experience the dance of jellyfish: float through mesmerizing swarms of jellyfish, pulsating with otherworldly grace and beauty.",
|
| 111 |
+
"__assets__/examples/t2v/1.mp4", "56 - frames", None, "ModelScopeT2V (text to video)", 33, 50, 9.0],
|
| 112 |
["People dancing in room filled with fog and colorful lights.",
|
| 113 |
+
"__assets__/examples/t2v/2.mp4", "56 - frames", None, "ModelScopeT2V (text to video)", 33, 50, 9.0],
|
| 114 |
["Discover the secret language of bees: delve into the complex communication system that allows bees to coordinate their actions and navigate the world.",
|
| 115 |
+
"__assets__/examples/t2v/3.mp4", "56 - frames", None, "AnimateDiff (text to video)", 33, 50, 9.0],
|
| 116 |
["sunset, orange sky, warm lighting, fishing boats, ocean waves seagulls, rippling water, wharf, silhouette, serene atmosphere, dusk, evening glow, coastal landscape, seaside scenery.",
|
| 117 |
+
"__assets__/examples/t2v/4.mp4", "56 - frames", None, "AnimateDiff (text to video)", 33, 50, 9.0],
|
| 118 |
["Dive into the depths of the ocean: explore vibrant coral reefs, mysterious underwater caves, and the mesmerizing creatures that call the sea home.",
|
| 119 |
+
"__assets__/examples/t2v/5.mp4", "56 - frames", None, "SVD (image to video)", 33, 50, 9.0],
|
| 120 |
["Ants, beetles and centipede nest.",
|
| 121 |
+
"__assets__/examples/t2v/6.mp4", "56 - frames", None, "SVD (image to video)", 33, 50, 9.0],
|
| 122 |
]
|
| 123 |
|
| 124 |
examples_2 = [
|
| 125 |
["Fishes swimming in ocean camera moving, cinematic.",
|
| 126 |
+
"__assets__/examples/i2v/1.mp4", "56 - frames", "__assets__/fish.jpg", "SVD (image to video)", 33, 50, 9.0],
|
| 127 |
["A squirrel on a table full of big nuts.",
|
| 128 |
+
"__assets__/examples/i2v/2.mp4", "56 - frames", "__assets__/squirrel.jpg", "SVD (image to video)", 33, 50, 9.0],
|
| 129 |
]
|
| 130 |
|
| 131 |
# --------------------------
|
|
|
|
| 216 |
|
| 217 |
inputs_v2v = [prompt_stage1, video_stage1, num_frames, image_stage1, model_name_stage1, model_name_stage2, seed, t, image_guidance]
|
| 218 |
|
| 219 |
+
inputs_examples = [prompt_stage1, video_stage2, num_frames, image_stage1, model_name_stage1, seed, t, image_guidance]
|
| 220 |
+
|
| 221 |
gr.HTML("""
|
| 222 |
<h2>
|
| 223 |
You can check the inference time for different number of frames
|
|
|
|
| 228 |
""")
|
| 229 |
|
| 230 |
gr.Examples(examples=examples_1,
|
| 231 |
+
inputs=inputs_examples,
|
| 232 |
+
# outputs=[video_stage2],
|
| 233 |
+
# fn=enhance,
|
| 234 |
+
# run_on_click=False,
|
| 235 |
+
# cache_examples=False,
|
| 236 |
)
|
| 237 |
|
| 238 |
gr.Examples(examples=examples_2,
|
| 239 |
+
inputs=inputs_examples,
|
| 240 |
+
# outputs=[video_stage2],
|
| 241 |
+
# fn=enhance,
|
| 242 |
+
# run_on_click=False,
|
| 243 |
+
# cache_examples=False,
|
| 244 |
+
# # preprocess=False,
|
| 245 |
+
# # postprocess=True,
|
| 246 |
)
|
| 247 |
|
| 248 |
run_button_stage2.click(fn=enhance, inputs=inputs_v2v, outputs=video_stage2,)
|