visualization update

app.py

@@ -3,6 +3,13 @@ import numpy as np
 import gradio as gr
 from infer import detections
 
+
+import os
+os.system("mkdir data")
+os.system("mkdir data/models")
+os.system("wget https://www.cs.cmu.edu/~walt/models/walt_people.pth -O data/models/walt_people.pth")
+os.system("wget https://www.cs.cmu.edu/~walt/models/walt_vehicle.pth -O data/models/walt_vehicle.pth")
+
 def walt_demo(input_img):
     #detect_people = detections('configs/walt/walt_people.py', 'cuda:0', model_path='data/models/walt_people.pth')
     detect = detections('configs/walt/walt_vehicle.py', 'cuda:0', model_path='data/models/walt_vehicle.pth')
@@ -34,15 +41,19 @@ article="""
 
 examples = [
     'demo/images/img_1.jpg',
+    'demo/images/img_2.jpg',
+    'demo/images/img_3.png',
+    'demo/images/img_4.png',
 ]
 
-
+'''
 import cv2
 filename='demo/images/img_1.jpg'
 img=cv2.imread(filename)
 img=walt_demo(img)
-cv2.imwrite(filename.replace('demo','demo/results/'),img)
-
+cv2.imwrite(filename.replace('/images/','/results/'),img)
+cv2.imwrite('check.png',img)
+'''
 demo = gr.Interface(walt_demo, 
         gr.Image(), 
         "image",
@@ -52,6 +63,7 @@ demo = gr.Interface(walt_demo,
         examples=examples,
         description=description)
 
-demo.launch(server_name="0.0.0.0", server_port=7000)
+#demo.launch(server_name="0.0.0.0", server_port=7000)
+demo.launch()
 
 

mmdet/core/visualization/image.py

@@ -165,13 +165,12 @@ def imshow_det_bboxes(img,
                 color_mask = mask_colors[np.random.randint(0, 99)]
                 mask = segms[len(labels)*ll+i].astype(bool)
                 show_border = True
-                #img[mask] = img[mask] * 0.5 + color_mask * 0.5
+                img[mask] = img[mask] * 0.5 + color_mask * 0.5
                 if show_border:
                     contours,_ = cv2.findContours(mask.copy().astype('uint8'), cv2.RETR_CCOMP, cv2.CHAIN_APPROX_NONE)
-                    border_thick = min(int(4*(max(bbox_int[2]-bbox_int[0],bbox_int[3]-bbox_int[1])/200))+1,6)
-                    print(border_thick, bbox_int)
-                    cv2.drawContours(img_bound, contours, -1, (int(color_mask[0][0]),int(color_mask[0][1]),int(color_mask[0][2])), border_thick)
-    img = cv2.addWeighted(img,1.0,img_bound,0.6,0)
+                    border_thick = min(int(4*(max(bbox_int[2]-bbox_int[0],bbox_int[3]-bbox_int[1])/300))+1,6)
+                    cv2.drawContours(img, contours, -1, (int(color_mask[0][0]),int(color_mask[0][1]),int(color_mask[0][2])), border_thick)
+    #img = cv2.addWeighted(img,1.0,img_bound,1.0,0)
     
     #img[img_bound>0] = img_bound
 

requirements.txt

@@ -0,0 +1,9 @@
+torch==1.9.0
+mmcv-full==1.4.0
+git+https://github.com/open-mmlab/mmdetection.git@7bd39044f35aec4b90dd797b965777541a8678ff
+gradio==3.0.20
+timm 
+scikit-image 
+imagesize
+torchvision==0.10.0
+imantics