yolov

app.ipynb

@@ -81,7 +81,7 @@
     "imgs = get_image_files('imgs')\n",
     "examples = [[imgs[0], 0, 0, 0.4, 0.225],[imgs[1], 0, 0.8, 0.225, 0.5]]\n",
     "iface = gr.Interface(fn=predict, title='DreamAI Object Detection',\n",
-    "                     description='Use dreamai to detect all obstacles in a certain area of an image.',\n",
+    "                     description='Use dreamai with yolov5 to detect all obstacles in a certain area of an image.',\n",
     "                     outputs=gr.Image(type=\"numpy\"), examples=examples,\n",
     "                     inputs=[gr.Image(type=\"numpy\"),\n",
     "                             gr.Slider(0, 1., 0.5, step=0.025, label='Box Top X (Relative)'),\n",

app.py

@@ -21,7 +21,7 @@ def predict(img, box_x=0, box_y=0, box_w=0.5, box_h=0.5, color='red'):
 imgs = get_image_files('imgs')
 examples = [[imgs[0], 0, 0, 0.4, 0.225],[imgs[1], 0, 0.8, 0.225, 0.5]]
 iface = gr.Interface(fn=predict, title='DreamAI Object Detection',
-                     description='Use dreamai to detect all obstacles in a certain area of an image.',
+                     description='Use dreamai with yolov5 to detect all obstacles in a certain area of an image.',
                      outputs=gr.Image(type="numpy"), examples=examples,
                      inputs=[gr.Image(type="numpy"),
                              gr.Slider(0, 1., 0.5, step=0.025, label='Box Top X (Relative)'),