Spaces:
Running
Running
Update app.py
Browse files
app.py
CHANGED
@@ -108,30 +108,131 @@ def process_image(image):
|
|
108 |
|
109 |
return Image.fromarray(img)
|
110 |
|
111 |
-
|
112 |
-
|
113 |
-
|
114 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
115 |
|
116 |
with gr.Tabs():
|
117 |
-
with gr.TabItem("Video Detection"):
|
118 |
-
with gr.Row():
|
119 |
-
video_input = gr.Video(label="Upload Video", interactive=True, elem_id="video-input")
|
120 |
-
process_button = gr.Button("Process Video", variant="primary", elem_id="video-process-btn")
|
121 |
-
video_output = gr.Video(label="Processed Video", elem_id="video-output")
|
122 |
-
process_button.click(fn=process_video, inputs=video_input, outputs=video_output)
|
123 |
-
|
124 |
-
with gr.TabItem("Image Detection"):
|
125 |
-
with gr.Row():
|
126 |
-
image_input = gr.Image(type="pil", label="Upload Image", interactive=True)
|
127 |
with gr.Row():
|
128 |
-
|
129 |
-
|
130 |
-
|
131 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
132 |
with gr.Row():
|
133 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
134 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
135 |
|
136 |
demo.launch()
|
137 |
-
|
|
|
108 |
|
109 |
return Image.fromarray(img)
|
110 |
|
111 |
+
css = """
|
112 |
+
#title {
|
113 |
+
text-align: center;
|
114 |
+
color: #2C3E50;
|
115 |
+
font-size: 2.5rem;
|
116 |
+
margin: 1.5rem 0;
|
117 |
+
text-shadow: 1px 1px 2px rgba(0,0,0,0.1);
|
118 |
+
}
|
119 |
+
|
120 |
+
.gradio-container {
|
121 |
+
background-color: #F5F7FA;
|
122 |
+
}
|
123 |
+
|
124 |
+
.tab-item {
|
125 |
+
background-color: white;
|
126 |
+
border-radius: 10px;
|
127 |
+
padding: 20px;
|
128 |
+
box-shadow: 0 4px 6px rgba(0,0,0,0.1);
|
129 |
+
margin: 10px;
|
130 |
+
}
|
131 |
+
|
132 |
+
.button-row {
|
133 |
+
display: flex;
|
134 |
+
justify-content: space-around;
|
135 |
+
margin: 1rem 0;
|
136 |
+
}
|
137 |
+
|
138 |
+
#video-process-btn, #submit-btn {
|
139 |
+
background-color: #3498DB;
|
140 |
+
border: none;
|
141 |
+
}
|
142 |
+
|
143 |
+
#clear-btn {
|
144 |
+
background-color: #E74C3C;
|
145 |
+
border: none;
|
146 |
+
}
|
147 |
+
|
148 |
+
.output-container {
|
149 |
+
margin-top: 1.5rem;
|
150 |
+
border: 2px dashed #3498DB;
|
151 |
+
border-radius: 10px;
|
152 |
+
padding: 10px;
|
153 |
+
}
|
154 |
+
|
155 |
+
.footer {
|
156 |
+
text-align: center;
|
157 |
+
margin-top: 2rem;
|
158 |
+
font-size: 0.9rem;
|
159 |
+
color: #7F8C8D;
|
160 |
+
}
|
161 |
+
"""
|
162 |
+
|
163 |
+
with gr.Blocks(css=css, title="Real-Time YOLOv5 Video & Image Object Detection") as demo:
|
164 |
+
gr.Markdown("""# Real-Time YOLOv5 Object Detection""", elem_id="title")
|
165 |
|
166 |
with gr.Tabs():
|
167 |
+
with gr.TabItem("Video Detection", elem_classes="tab-item"):
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
168 |
with gr.Row():
|
169 |
+
video_input = gr.Video(
|
170 |
+
label="Upload Video",
|
171 |
+
interactive=True,
|
172 |
+
elem_id="video-input"
|
173 |
+
)
|
174 |
+
|
175 |
+
with gr.Row(elem_classes="button-row"):
|
176 |
+
process_button = gr.Button(
|
177 |
+
"Process Video",
|
178 |
+
variant="primary",
|
179 |
+
elem_id="video-process-btn"
|
180 |
+
)
|
181 |
+
|
182 |
+
with gr.Row(elem_classes="output-container"):
|
183 |
+
video_output = gr.Video(
|
184 |
+
label="Processed Video",
|
185 |
+
elem_id="video-output"
|
186 |
+
)
|
187 |
+
|
188 |
+
process_button.click(
|
189 |
+
fn=process_video,
|
190 |
+
inputs=video_input,
|
191 |
+
outputs=video_output
|
192 |
+
)
|
193 |
+
|
194 |
+
with gr.TabItem("Image Detection", elem_classes="tab-item"):
|
195 |
with gr.Row():
|
196 |
+
image_input = gr.Image(
|
197 |
+
type="pil",
|
198 |
+
label="Upload Image",
|
199 |
+
interactive=True
|
200 |
+
)
|
201 |
+
|
202 |
+
# Define image_output before it's referenced
|
203 |
+
image_output = gr.Image(
|
204 |
+
label="Detected Objects",
|
205 |
+
elem_id="image-output"
|
206 |
+
)
|
207 |
+
|
208 |
+
with gr.Row(elem_classes="button-row"):
|
209 |
+
clear_button = gr.Button(
|
210 |
+
"Clear",
|
211 |
+
variant="secondary",
|
212 |
+
elem_id="clear-btn"
|
213 |
+
)
|
214 |
+
submit_button = gr.Button(
|
215 |
+
"Detect Objects",
|
216 |
+
variant="primary",
|
217 |
+
elem_id="submit-btn"
|
218 |
+
)
|
219 |
+
|
220 |
+
# Now the clear_button can reference image_output
|
221 |
+
clear_button.click(
|
222 |
+
fn=lambda: None,
|
223 |
+
inputs=None,
|
224 |
+
outputs=image_output
|
225 |
+
)
|
226 |
|
227 |
+
submit_button.click(
|
228 |
+
fn=process_image,
|
229 |
+
inputs=image_input,
|
230 |
+
outputs=image_output
|
231 |
+
)
|
232 |
+
|
233 |
+
gr.Markdown("""
|
234 |
+
### Powered by YOLOv5.
|
235 |
+
This application allows real-time object detection using the YOLOv5 model.
|
236 |
+
""", elem_classes="footer")
|
237 |
|
238 |
demo.launch()
|
|