Update app.py

app.py

@@ -7,7 +7,7 @@ import gradio as gr
 
 #cap = cv2.VideoCapture(0)
 detector = HandDetector(maxHands=1)
-classifier = Classifier("Model/keras_model.h5", "Model/labels.txt")
+classifier = Classifier("ModelFull/keras_model.h5", "ModelFull/labels.txt")
 
 offset = 20
 imgSize = 300
@@ -15,7 +15,7 @@ imgSize = 300
 folder = "Data/C"
 counter = 0
 
-labels = ["A", "B"]
+labels = ["A", "B","C","D","E","F","G","H","I","J","K","L","M","N", "O","P","Q","R","S","T","U","V","W","X","Y","Z"]
 
 
 def sign(img):
@@ -60,9 +60,9 @@ def sign(img):
         #cv2.rectangle(imgOutput, (x - offset, y - offset-50),
         #              (x - offset+90, y - offset-50+50), (255, 0, 255), cv2.FILLED)
         #cv2.putText(imgOutput, labels[index], (x, y -26), cv2.FONT_HERSHEY_COMPLEX, 1.7, (255, 255, 255), 2)
-        cv2.rectangle(imgOutput, (30,30),
+        cv2.rectangle(imgOutput, (0,30),
                       (80,80), (255, 0, 255), cv2.FILLED)
-        cv2.putText(imgOutput, labels[index], (30, 80), cv2.FONT_HERSHEY_COMPLEX, 1.7, (255, 255, 255), 2)
+        cv2.putText(imgOutput, labels[index], (20, 75), cv2.FONT_HERSHEY_COMPLEX, 1.7, (255, 255, 255), 2)
 
 
         #cv2.imshow("ImageCrop", imgCrop)
@@ -86,4 +86,4 @@ with gr.Blocks() as demo:
         inputs = img_input2,
         outputs = output2) 
 
-demo.launch(debug=True)
+demo.launch(debug=True)