Example #1
0
    def post(self):
        resp = {"result": str(-1)}
        data = self.get_arguments("data[]")

        validated = Validator.validate_data(data)
        machine = MachineLoader.load(machines.number_recognizer)

        #save train data
#        with open('C:/Github/number_recognizer/train_1.txt','a') as thefile:
#            for item in validated:
#                thefile.write("%s\t" %item)
#            thefile.write("\n")

        #save target data
#        b = self.get_arguments("b")
#        with open('C:/Github/number_recognizer/target_1.txt','a') as thefile:
#            thefile.write(b[0])
#            thefile.write("\n")


        if len(validated) > 0:
            predicted = machine.predict(validated)
            resp["result"] = str(predicted[0])

        self.write(resp)
Example #2
0
    def post(self):
        resp = {"result": str(-1)}
        data = self.get_arguments("data[]")
        new_number= self.get_arguments("new_number")
        print(new_number)

        validated = Validator.validate_data(data)
        machine = MachineLoader.load(machines.number_recognizer)

        with open('C:/git_number/number_recognizer/data_text.txt','a') as thefile:
            for item in validated:
                thefile.write("%s" % item)
            thefile.write("\n")

        with open('C:/git_number/number_recognizer/new_number.txt','a') as thefile:
            for item in new_number:
                thefile.write("%s" % item)
            thefile.write("\n")


        if len(validated) > 0:
            predicted = machine.predict(validated)
            resp["result"] = str(predicted[0])

        self.write(resp)
Example #3
0
    def post(self):
        resp = {"result": str(-1)}
        data = self.get_arguments("data[]")

        validated = Validator.validate_data(data)
        machine = MachineLoader.load(machines.number_recognizer)
        if len(validated) > 0:
            predicted = machine.predict(validated)
            resp["result"] = str(predicted[0])

        self.write(resp)
Example #4
0
    def post(self):
        resp = {"result": str(-1)}
        data = self.get_arguments("data[]")

        validated = Validator.validate_data(data)
        machine = MachineLoader.load(machines.number_recognizer)
        if len(validated) > 0:
            predicted = machine.predict(np.array(validated).reshape(1, -1))
            resp["result"] = str(predicted[0])

        self.write(resp)
Example #5
0
    def post(self):
        data = self.get_arguments("data[]")
        result = ""

        feedback = Validator.validate_feedback(data)
        if len(feedback) > 0:
            MachineLoader.feedback(machines.number_recognizer, feedback)
        else:
            result = "feedback format is wrong."

        resp = {"result": result}
        self.write(resp)
Example #6
0
    def post(self):
        data = self.get_arguments("data[]")
        result = ""

        feedback = Validator.validate_feedback(data)
        if len(feedback) > 0:
            MachineLoader.feedback(machines.number_recognizer, feedback)
        else:
            result = "feedback format is wrong."

        resp = {"result": result}
        self.write(resp)
Example #7
0
    def post(self):
        resp = {"result": str(-1)}
        data = self.get_arguments("data[]")
        validated = Validator.validate_data(data)

        # machine = MachineLoader.load(machines.number_recognizer)
        # if len(validated) > 0:
        #     predicted = machine.predict(validated)
        #     resp["result"] = str(predicted[0])
        # number_recognizer.train()

        result = number_recognizer.test(validated)
        resp["result"] = str(result)
        self.write(resp)
Example #8
0
    def post(self):
        resp = {"result": str(-1)}
        data = self.get_arguments("data[]")
#        new_number = self.get_arguments("new_number")
        #print(new_number)

        validated = Validator.validate_data(data)
        machine = MachineLoader.load(machines.number_recognizer)
        if len(validated) > 0:
            predicted = machine.predict(validated)
            #print(validated)
#            import numpy as np
#            import scipy
            #scipy.mise.toimage(np.array(validated).reshape(8,8), cmin=0.0, cmax=16).save('outfile.jpg')
            resp["result"] = str(int(predicted[0]))
        self.write(resp)
Example #9
0
    def post(self):
        data = self.get_arguments("data[]")
        result = ""

        feedback = Validator.validate_feedback(data)
        if len(feedback) > 0:
            # save feedback to file
            MachineLoader.feedback(machines.number_recognizer, feedback)

            # online training
            machine = MachineLoader.load(machines.number_recognizer)
            machine.partial_fit(feedback[1:], [feedback[0]])
            MachineLoader.save(machines.number_recognizer, machine)
        else:
            result = "feedback format is wrong."

        resp = {"result": result}
        self.write(resp)
Example #10
0
    def post(self):
        data = self.get_arguments("data[]")
        result = ""

        feedback = Validator.validate_feedback(data)
        if len(feedback) > 0:
            # save feedback to file
            MachineLoader.feedback(machines.number_recognizer, feedback)

            # online training
            machine = MachineLoader.load(machines.number_recognizer)
            machine.partial_fit(feedback[1:], [feedback[0]])
            MachineLoader.save(machines.number_recognizer, machine)
        else:
            result = "feedback format is wrong."

        resp = {"result": result}
        self.write(resp)
Example #11
0
    def post(self):
        resp = {"result": str(-1)}
        data = self.get_arguments("data[]")

        validated = Validator.validate_data(data)
        machine = MachineLoader.load(machines.number_recognizer)

        with open('c:/temp/test.txt','a') as thefile:
            for item in validated:
                thefile.write("%s\n" % item)
        from random import randint
        b=randint(0,9)
        print("please input number %d" % b)
        with open('c:/temp/target.txt','a') as thefile:
            thefile.write("%s\n" % b)
        if len(validated) > 0:
            predicted = machine.predict(validated)
            print(validated)
            print(predicted)
            resp["result"] = str(predicted[0])
            #resp["result"] = str(b)

        self.write(resp)