Implementing critical solution part I

AI/api_caller.py

@@ -31,29 +31,15 @@ def turn_right(self, angle):
 
     def move_forward(self, cm):
 
-        params = {'cm': 1}
-        i = 0
-
-        while i < cm:
-
-            try:
-                self.logger.debug('Sending move_forward request ({0} cm)'.format(cm))
-                response = requests.get(self.url + '/move/forward', params=params, timeout=self.timeout)
-                is_in_range_response = requests.get(self.url + '/trash/isinrange', timeout=self.timeout)
-            except requests.exceptions.Timeout:
-                self.logger.warn('move_forward timeout exception')
-                #return False
-
-            if not response.ok or not is_in_range_response.ok:
-                self.logger.error('Response is not OK')
-                #return False
-
-            #self.logger.debug('Response: ' + str(response.json()))
-            if is_in_range_response.json() == True:
-                return True
+        params = {'cm': cm}        
 
+        try:
+            self.logger.debug('Sending move_forward request ({0} cm)'.format(cm))
+            requests.get(self.url + '/move/forward', params=params, timeout=self.timeout)
+        except requests.exceptions.Timeout:
+            self.logger.warn('move_forward timeout exception')
 
-        return False
+        return True
 
     def is_in_range(self):
         """
@@ -83,7 +69,7 @@ def pick_up(self):
 
     def __send_turn_request(self, angle):
 
-        params = {'angle': angle / 3}
+        params = {'angle': angle}
         try:
             self.logger.debug('Sending turn request ({0} angle)'.format(angle))
             response = requests.get(self.url + '/move/turn', params=params, timeout=self.timeout)

AI/image_func.py

@@ -16,5 +16,4 @@ def get_img():
     else:
         img.save(destination + '.jpg')
         img = cv2.imread(destination + '.jpg')
-
     return img

AI/main.py

@@ -108,6 +108,9 @@ def navigate_to_bottle(result):
     logging.debug('result of detection: ')
     logging.debug(result)
     process_result = process_bottle(result[0][1:-1])
+    if process_result != move_enum.FORWARD:
+        api.move_forward(500)
+    raise ValueError('Sorry, model hasn´t been trained pretty well, we cannot continue ...')
 
     while True:
         img = get_img()
@@ -129,17 +132,24 @@ def navigate_to_bottle(result):
 
 
 def ultimate_finding_cycle():
-
+    num_of_turns = 0
     while True:
         img = get_img()
         yolo.detect_from_cvmat(img)
         result = filter_results(yolo.result)
         if len(result) == 1:
+            print('Woooow, I got an image')
             navigate_to_bottle(result)
             break
         else:
+            num_of_turns += 1
             logging.debug('ultimate_finding_cycle can´t see anythink')
-            api.turn_right(10)
+            if num_of_turns < 4:
+                api.turn_right(10)
+            else:
+                api.turn_left(10)
+                if num_of_turns == 8:
+                    num_of_turns = 0
             #api.move_forward(1)
 
 

AI/test.py

@@ -1,14 +1,21 @@
 # -*- coding: utf-8 -*-
-from YOLO_small_tf import YOLO_TF
-import time
+import cv2
+import numpy as np
 
-yolo = YOLO_TF()
+def is_cell_red(cell):
+    return cell[3] > 180
 
-yolo.imshow = False
-s = time.time()
-yolo.detect_from_file('resources/test.jpg')
-print('Detection time: ' + str(time.time()-s))
+def check_row(row):
+    distance = 0
+    large = 0
+    
 
-result = yolo.result
+def detect(image):
+    # BGR
+    largest_distance = 0
+    for row in np.array(image)[0]:
+        print(row)
+
+
 
-print('result')
+detect(cv2.imread('resources/test_img.PNG'))