0.0.1a

2022-06-30 22:15:11 +03:00
parent 8c3ee11b4e
commit ae846f2e3e
6 changed files with 102 additions and 0 deletions
@@ -1,3 +1,10 @@
+# Test files
+
+data/vids/*
+data/screen/*
+data/json/*
+data/*.*
+
 # Byte-compiled / optimized / DLL files
 __pycache__/
 *.py[cod]
@@ -0,0 +1,11 @@
+<html>
+    <head>
+        <title>{file_name}</title>
+    </head>
+    <h2>{file_name}</h2><br>
+    <h3>{resolution}</h3><br>
+    <h3>{duration}</h3><br>
+    <video height="50%" src="{file_vid}" controls></video><br>
+    <hr>
+    {frame_info}
+</html>
@@ -0,0 +1,6 @@
+<div>
+    <p>{file_name}</p>
+    <img src="{file_name}" alt="{file_name}" height="50%"><br>
+    <p>{info_res}</p>
+</div>
+<hr>
@@ -0,0 +1,30 @@
+import json
+
+
+def create(file_name):
+    datas = json.load(open("data/json/"+file_name+".json", "r", encoding='utf-8'))
+    text_no_format = open("data/templates/index.html", "r").read()
+    text_f_no_format = open("data/templates/one_frame.html", "r").read()
+    list_frame_id = datas["frames"].keys()
+    text_f_format = ""
+    for ii in list_frame_id:
+        res_info=""
+        for dd in datas["frames"][ii].keys():
+            if dd == "file":
+                pass
+            else:
+                res_add = dd + " : " +str(round(datas["frames"][ii][dd]*100, 2))+"<br>"
+                res_info += res_add
+        text_add = text_f_no_format.format(
+            file_name=datas["frames"][ii]["file"],
+            info_res=res_info
+        )
+        text_f_format += text_add
+    text_format = text_no_format.format(
+        file_name=file_name,
+        resolution=str(round(datas["height"]))+"x"+str(round(datas["width"])),
+        duration=str(round(datas["duration"], 2))+" s.",
+        file_vid="vids/"+file_name,
+        frame_info=text_f_format
+    )
+    open("data/"+file_name+".html", "w").write(text_format)
@@ -0,0 +1,48 @@
+import PIL.Image as Image
+from nsfw_detector import predict
+import cv2
+import os
+import json
+import html_create
+
+def save_frame(screen_folder, secs, vid):
+    save_name = screen_folder + "/" + str(secs) + ".jpg"
+    fps = vid.get(cv2.CAP_PROP_FPS)
+    vid.set(cv2.CAP_PROP_POS_FRAMES, fps*secs)
+    ret, frame = vid.read()
+    cv2.imwrite(save_name, frame)
+    return save_name
+
+model = predict.load_model('./data/model/nsfw_mobilenet2.224x224.h5')
+file_path = "./data/vids/5.mp4"
+vid = cv2.VideoCapture( file_path )
+height = vid.get(cv2.CAP_PROP_FRAME_HEIGHT)
+width = vid.get(cv2.CAP_PROP_FRAME_WIDTH) 
+fps = vid.get(cv2.CAP_PROP_FPS)
+totalNoFrames = vid.get(cv2.CAP_PROP_FRAME_COUNT)
+durationInSeconds = float(totalNoFrames) / float(fps)
+datas = {"height":height, "width":width, "duration":durationInSeconds}
+print(height, width, durationInSeconds)
+screen_folder = "data/screen/" + file_path.split("/")[-1]
+try:
+    if not os.path.exists(screen_folder):
+        os.makedirs(screen_folder)
+except OSError:
+    print('Error: Creating directory of data')
+save_frame(screen_folder, 1, vid)
+current_sec = 1
+datas_frames = {}
+while True:
+    if current_sec < durationInSeconds:  
+        file_name = save_frame(screen_folder, current_sec, vid)
+        image = Image.open(file_name)
+        data_res = predict.classify(model, file_name)
+        data_one = data_res[list(data_res.keys())[0]]
+        data_one["file"] = file_name.replace("data/", "", 1)
+        datas_frames[str(current_sec)] = data_one
+    else:
+        break
+    current_sec += 5
+datas["frames"] = datas_frames
+json.dump(datas, open("data/json/"+file_path.split("/")[-1]+".json", "w", encoding='utf-8'), ensure_ascii=False, indent=4)
+html_create.create(file_path.split("/")[-1])