Merge branch 'master' of https://github.com/fedingo/MCPS-FridgePI

WebServer/ImageRec.py

@@ -1,5 +1,7 @@
 import Mask_RCNN.model as modellib
 import Mask_RCNN.coco as coco
+import Mask_RCNN.visualize as visualize
+import os.path
 
 class InferenceConfig(coco.CocoConfig):
     # Set batch size to 1 since we'll be running inference on
@@ -29,6 +31,9 @@ class ImageRec:
     def __init__(self):
         model_path = "Mask_RCNN/mask_rcnn_coco.h5"
 
+        if not os.path.isfile(model_path):
+            raise ValueError(500, "Mask-RCNN missing image segmentation model")
+
         configuration = InferenceConfig()
 
         # Create model object in inference mode.
@@ -44,6 +49,10 @@ def recognize(self, image):
         result = self.model.detect([image], verbose=1)[0]
         result['objects'] = []
 
+        r = result
+        visualize.display_instances(image, r['rois'], r['masks'], r['class_ids'],
+                                    self.class_names, r['scores'])
+
         for i in result['class_ids']:
             result['objects'].append(self.class_names[i])
 

WebServer/Mask_RCNN/visualize.py

@@ -17,8 +17,9 @@
 import matplotlib.lines as lines
 from matplotlib.patches import Polygon
 import IPython.display
+from PIL import Image
 
-import utils
+import Mask_RCNN.utils
 
 
 ############################################################
@@ -143,8 +144,11 @@ def display_instances(image, boxes, masks, class_ids, class_names,
             p = Polygon(verts, facecolor="none", edgecolor=color)
             ax.add_patch(p)
     ax.imshow(masked_image.astype(np.uint8))
-    plt.show()
-
+    im = Image.fromarray(masked_image.astype(np.uint8))
+    im.save("received.jpeg")
+    #plt.show()
+    #plt.imsave(fname = "matplot.jpg", arr = masked_image.astype(np.uint8))
+
 
 def draw_rois(image, rois, refined_rois, mask, class_ids, class_names, limit=10):
     """

WebServer/Recipes_Finder.py

@@ -19,7 +19,8 @@ def findRecipes(username, password, max_results):
     ingred_params = ""
 
     for item in ingredients:
-        ingred_params += item + ","
+        string = item.replace(' ','')
+        ingred_params += string + ","
 
     ingred = ingred_params[:-1]
 
@@ -33,3 +34,6 @@ def findRecipes(username, password, max_results):
     response = urlopen(request).read().decode()
 
     return json.loads(response)['recipes'][0:max_results]
+
+
+# http://food2fork.com/api/search?key=42fdbda9d0108cfcc9793dcc8051cd7f&q=tuna,beans,pasta