diff --git a/Events/src/myproject2.py b/Events/src/myproject2.py index edcbe6b..1a0992f 100644 --- a/Events/src/myproject2.py +++ b/Events/src/myproject2.py @@ -10,46 +10,26 @@ app = Flask(__name__) app.config["IMAGE_UPLOADS"] = "C:/Users/Bizgaze/PycharmProjects/face_recogniction/People" #datasetPath = "/opt/bizgaze/events.bizgaze.app/wwwroot/_files/1/Gallery/" #peoplePath = "/opt/bizgaze/events.bizgaze.app/wwwroot/_files/People/" + + + + @app.route('/', methods=['GET']) def home(): return render_template('index.html') -@app.route('/Display', methods=['GET', "POST"]) -def Display(): - return render_template('Display.html') - - -@app.route("/upload", methods=["GET", "POST"]) -def upload(): - if request.method == "POST": - - if request.files: - - image = request.files["image"] - try: - image.save(os.path.join( - app.config["IMAGE_UPLOADS"], image.filename)) - except IsADirectoryError: - return render_template('index.html') - # image.save(os.path.join( - # app.config["IMAGE_UPLOADS"], image.filename)) - - print("Image saved") - - return redirect(request.url) - - return 'ok' - @app.route('/predict', methods=["GET", "POST"]) def predict(): Dataset = request.get_json() a = Dataset peoplePath = a['People'] - print(peoplePath) + + #print(peoplePath1) datasetPath = a['Gallery'] - print(datasetPath) + + #print(datasetPath) print('starting') def saveEncodings(encs, names, fname="encodings.pickle"): @@ -200,7 +180,9 @@ def predict(): if os.path.exists(path): pass else: - os.mkdir(path) + if not os.path.exists(path): + os.makedirs(path) + # os.mkdir(path,exist_ok=True) cv2.imwrite(path + "/" + imageName, image) x = [] c = (path1 + "/" + imageName) @@ -331,8 +313,8 @@ def predict(): """ - processKnownPeopleImages() - processDatasetImages() + processKnownPeopleImages(peoplePath) + processDatasetImages(datasetPath) # shutil.make_archive('./Images', 'zip','./output') # p='./Images.zip' # return send_file(p,as_attachment=True) @@ -364,7 +346,6 @@ def predict(): df.rename(columns={first_column_name: 'col'}, inplace=True) #print(df) z = df['col'].str.split('/', expand=True) - z['ImagePath'] = z[3] result = z.drop([0,1,3], axis=1) @@ -387,7 +368,7 @@ def predict(): # Rename the first column df.rename(columns={first_column_name: 'col'}, inplace=True) print(df) - df1 = df['col'].str.split("/", expand=True) + df1 = df['col'].str.split("\\", expand=True) df1.rename({df1.columns[-2]: 'abc'}, axis=1, inplace=True) #print('this is df1') #print(df1) @@ -400,7 +381,7 @@ def predict(): merge.rename({merge.columns[-1]: 'Matched'}, axis=1, inplace=True) merge['EventName'] = merge['abc'] - merge['Imagepath']="/_files/1/Gallery/"+merge['EventName']+'/'+ + merge['test'] + merge['Imagepath']= datasetPath+merge['EventName']+'/'+ + merge['test'] frames = [merge, mergesplit] @@ -414,85 +395,6 @@ def predict(): ############################################################################################# - - - # merge.rename({merge.columns[-3]: 'ImagePath'}, axis=1, inplace=True) - # - # # print(merge) - # merge1 = merge.iloc[:, -2] - # merge12= merge.iloc[:, -3] - # - # # merge1.rename({merge1.columns[-1]: 'abc'}, axis=1, inplace=True) - # merge2 = merge.iloc[:, -1].str.split(".", expand=True) - # merge2.rename({merge2.columns[-1]: 'drop'}, axis=1, inplace=True) - # #merge2.rename({merge2.columns[-2]: 'ImageName'}, axis=1, inplace=True) - # print('this is merge1') - # print(merge1) - # print('this is merge2') - # print(merge2) - # mergefinal = pd.concat([merge1, merge2], axis=1, join='inner') - # # print(mergefinal) - # # print('-----------------') - # - # mergefinal.drop(columns=mergefinal.columns[-1], axis=1, inplace=True) - # # print(mergefinal) - # # print('--------------------------------------------------------------------------------') - # # mergefinal.rename({mergefinal.columns[-1]: 'ImageName'}, axis=1, inplace=True) - # # print('this is filename') - # # print(mergefinal) - # #mergefinal.rename({mergefinal.columns[-2]: 'EventName'}, axis=1, inplace=True) - # # print('this is foldername') - # # print(mergefinal) - # - # frames = [mergefinal, merge12] - # - # r = pd.concat(frames, axis=1, join='inner') - # - # - # r.to_csv('Imagepath1.csv', index=False) - # r.to_json('Imagepath1.json', orient="records") - # import shutil - # import os - # # import shutil module - # import shutil - # - # # import os module - # import os - # #################### move code############# - # # base path - # base_path = 'C:\\Users\\Bizgaze\\PycharmProjects\\face_recogniction\\move' - # import os - # dir_list = [] - # rootdir = 'C:\\Users\\Bizgaze\\PycharmProjects\\face_recogniction\\Dataset' - # for file in os.listdir(rootdir): - # d = os.path.join(rootdir, file) - # if os.path.isdir(d): - # dir_list.append(d) - # - # # list of directories we want to move. - # # dir_list = ['test2', 'test4', 'test5', 'does_not_exist'] - # - # # path to destination directory - # # dest = os.path.join(base_path, 'dest') - # - # print("Before moving directories:") - # print(os.listdir(base_path)) - # - # # traverse each directory in dir_list - # for dir_ in dir_list: - # - # # create path to the directory in the - # # dir_list. - # source = os.path.join(base_path, dir_) - # - # # check if it is an existing directory - # if os.path.isdir(source): - # # move to destination path - # shutil.move(source, base_path) - # - # print("After moving directories:") - # print(os.listdir(base_path)) - print("Completed") if __name__ == "__main__":