Spaces:
Running
on
Zero
Running
on
Zero
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: π
|
|
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)
|