Spaces:
Runtime error
Runtime error
fix bug
Browse files- README.md +1 -1
- __pycache__/transforms.cpython-310.pyc +0 -0
- app.py +33 -27
README.md
CHANGED
|
@@ -4,7 +4,7 @@ emoji: 🐍
|
|
| 4 |
colorFrom: blue
|
| 5 |
colorTo: green
|
| 6 |
sdk: gradio
|
| 7 |
-
sdk_version:
|
| 8 |
app_file: app.py
|
| 9 |
pinned: false
|
| 10 |
license: apache-2.0
|
|
|
|
| 4 |
colorFrom: blue
|
| 5 |
colorTo: green
|
| 6 |
sdk: gradio
|
| 7 |
+
sdk_version: 4.21.0
|
| 8 |
app_file: app.py
|
| 9 |
pinned: false
|
| 10 |
license: apache-2.0
|
__pycache__/transforms.cpython-310.pyc
CHANGED
|
Binary files a/__pycache__/transforms.cpython-310.pyc and b/__pycache__/transforms.cpython-310.pyc differ
|
|
|
app.py
CHANGED
|
@@ -1,8 +1,13 @@
|
|
| 1 |
import os
|
|
|
|
| 2 |
|
| 3 |
# install packages for mamba
|
| 4 |
-
|
| 5 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
| 6 |
|
| 7 |
import torch
|
| 8 |
import torch.nn as nn
|
|
@@ -25,7 +30,6 @@ import gradio as gr
|
|
| 25 |
from huggingface_hub import hf_hub_download
|
| 26 |
|
| 27 |
|
| 28 |
-
|
| 29 |
# Device on which to run the model
|
| 30 |
# Set to cuda to load on GPU
|
| 31 |
device = "cuda"
|
|
@@ -87,6 +91,7 @@ def load_video(video_path):
|
|
| 87 |
return torch_imgs
|
| 88 |
|
| 89 |
|
|
|
|
| 90 |
def inference_video(video):
|
| 91 |
vid = load_video(video)
|
| 92 |
|
|
@@ -105,6 +110,7 @@ def set_example_video(example: list) -> dict:
|
|
| 105 |
return gr.Video.update(value=example[0])
|
| 106 |
|
| 107 |
|
|
|
|
| 108 |
def inference_image(img):
|
| 109 |
image = img
|
| 110 |
image_transform = T.Compose(
|
|
@@ -141,30 +147,30 @@ with demo:
|
|
| 141 |
)
|
| 142 |
|
| 143 |
with gr.Tab("Video"):
|
| 144 |
-
with gr.Box():
|
| 145 |
-
|
| 146 |
-
|
| 147 |
-
|
| 148 |
-
|
| 149 |
-
|
| 150 |
-
|
| 151 |
-
|
| 152 |
-
|
| 153 |
-
|
| 154 |
-
|
| 155 |
|
| 156 |
with gr.Tab("Image"):
|
| 157 |
-
with gr.Box():
|
| 158 |
-
|
| 159 |
-
|
| 160 |
-
|
| 161 |
-
|
| 162 |
-
|
| 163 |
-
|
| 164 |
-
|
| 165 |
-
|
| 166 |
-
|
| 167 |
-
|
| 168 |
|
| 169 |
gr.Markdown(
|
| 170 |
"""
|
|
@@ -173,9 +179,9 @@ with demo:
|
|
| 173 |
)
|
| 174 |
|
| 175 |
submit_video_button.click(fn=inference_video, inputs=input_video, outputs=label_video)
|
| 176 |
-
example_videos.click(fn=set_example_video, inputs=example_videos, outputs=example_videos.
|
| 177 |
submit_image_button.click(fn=inference_image, inputs=input_image, outputs=label_image)
|
| 178 |
-
example_images.click(fn=set_example_image, inputs=example_images, outputs=example_images.
|
| 179 |
|
| 180 |
demo.launch(enable_queue=True)
|
| 181 |
# demo.launch(server_name="0.0.0.0", server_port=10034, enable_queue=True)
|
|
|
|
| 1 |
import os
|
| 2 |
+
import spaces
|
| 3 |
|
| 4 |
# install packages for mamba
|
| 5 |
+
@spaces.GPU
|
| 6 |
+
def install():
|
| 7 |
+
print("Install personal packages", flush=True)
|
| 8 |
+
os.system("bash install.sh")
|
| 9 |
+
|
| 10 |
+
install()
|
| 11 |
|
| 12 |
import torch
|
| 13 |
import torch.nn as nn
|
|
|
|
| 30 |
from huggingface_hub import hf_hub_download
|
| 31 |
|
| 32 |
|
|
|
|
| 33 |
# Device on which to run the model
|
| 34 |
# Set to cuda to load on GPU
|
| 35 |
device = "cuda"
|
|
|
|
| 91 |
return torch_imgs
|
| 92 |
|
| 93 |
|
| 94 |
+
@spaces.GPU
|
| 95 |
def inference_video(video):
|
| 96 |
vid = load_video(video)
|
| 97 |
|
|
|
|
| 110 |
return gr.Video.update(value=example[0])
|
| 111 |
|
| 112 |
|
| 113 |
+
@spaces.GPU
|
| 114 |
def inference_image(img):
|
| 115 |
image = img
|
| 116 |
image_transform = T.Compose(
|
|
|
|
| 147 |
)
|
| 148 |
|
| 149 |
with gr.Tab("Video"):
|
| 150 |
+
# with gr.Box():
|
| 151 |
+
with gr.Row():
|
| 152 |
+
with gr.Column():
|
| 153 |
+
with gr.Row():
|
| 154 |
+
input_video = gr.Video(label='Input Video').style(height=360)
|
| 155 |
+
with gr.Row():
|
| 156 |
+
submit_video_button = gr.Button('Submit')
|
| 157 |
+
with gr.Column():
|
| 158 |
+
label_video = gr.Label(num_top_classes=5)
|
| 159 |
+
with gr.Row():
|
| 160 |
+
example_videos = gr.Dataset(components=[input_video], samples=[['./videos/hitting_baseball.mp4'], ['./videos/hoverboarding.mp4'], ['./videos/yoga.mp4']])
|
| 161 |
|
| 162 |
with gr.Tab("Image"):
|
| 163 |
+
# with gr.Box():
|
| 164 |
+
with gr.Row():
|
| 165 |
+
with gr.Column():
|
| 166 |
+
with gr.Row():
|
| 167 |
+
input_image = gr.Image(label='Input Image', type='pil').style(height=360)
|
| 168 |
+
with gr.Row():
|
| 169 |
+
submit_image_button = gr.Button('Submit')
|
| 170 |
+
with gr.Column():
|
| 171 |
+
label_image = gr.Label(num_top_classes=5)
|
| 172 |
+
with gr.Row():
|
| 173 |
+
example_images = gr.Dataset(components=[input_image], samples=[['./images/cat.png'], ['./images/dog.png'], ['./images/panda.png']])
|
| 174 |
|
| 175 |
gr.Markdown(
|
| 176 |
"""
|
|
|
|
| 179 |
)
|
| 180 |
|
| 181 |
submit_video_button.click(fn=inference_video, inputs=input_video, outputs=label_video)
|
| 182 |
+
example_videos.click(fn=set_example_video, inputs=example_videos, outputs=example_videos._components)
|
| 183 |
submit_image_button.click(fn=inference_image, inputs=input_image, outputs=label_image)
|
| 184 |
+
example_images.click(fn=set_example_image, inputs=example_images, outputs=example_images._components)
|
| 185 |
|
| 186 |
demo.launch(enable_queue=True)
|
| 187 |
# demo.launch(server_name="0.0.0.0", server_port=10034, enable_queue=True)
|