Update app.py

app.py

@@ -69,6 +69,7 @@ def plot_flows(y):
 
 def plot_outlines(img, masks):
     img = normalize99(img)
+    img = np.clip(img, 0, 1)
     outpix = []
     contours, hierarchy = cv2.findContours(masks.astype(np.int32), mode=cv2.RETR_FLOODFILL, method=cv2.CHAIN_APPROX_SIMPLE)
     for c in range(len(contours)):
@@ -118,8 +119,7 @@ def plot_overlay(img, masks):
         img_gray = img.astype(np.float32)
         
     img = normalize99(img_gray)
-    img -= img.min()
-    img /= img.max()
+    #img = np.clip(img, 0, 1)
     HSV = np.zeros((img.shape[0], img.shape[1], 3), np.float32)
     HSV[:,:,2] = np.clip(img*1.5, 0, 1.0)
     for n in range(int(masks.max())):
@@ -224,8 +224,8 @@ def cellpose_segment(filepath, resize = 1000,max_iter = 250):
     fname_out  = os.path.splitext(filepath[-1])[0]+"_outlines.png"
     outpix.save(fname_out) #"outlines.png")
     
-    fname_flows  = os.path.splitext(filepath[-1])[0]+"_flows.png"
-    flows.save(fname_flows) #"outlines.png")
+    #fname_flows  = os.path.splitext(filepath[-1])[0]+"_flows.png"
+    #flows.save(fname_flows) #"outlines.png")
 
     if len(filepath)>1:
         b1 = gr.DownloadButton(visible=True, value = zip_path)
@@ -235,15 +235,6 @@ def cellpose_segment(filepath, resize = 1000,max_iter = 250):
     
     return outpix, flows, b1, b2
 
-# Gradio Interface
-#iface = gr.Interface(
-#    fn=cellpose_segment, 
-#    inputs="image", 
-#    outputs=["image", "image", "image", "image"],
-#    title="cellpose segmentation",
-#    description="upload an image, then cellpose will segment it at a max size of 400x400 (for full functionality, 'pip install cellpose' locally)"
-#)
-
 def download_function(): 
     b1 = gr.DownloadButton("Download masks as TIFF", visible=False)
     b2 = gr.DownloadButton("Download outline image as PNG", visible=False)