Update app.py

app.py

@@ -87,13 +87,13 @@ class VideoClassifier:
         start = time.time()
         mp4_file = video_input
         video_name = mp4_file.split("/")[-1]
-        wav_file = "results/audiotrack.wav"
+        wav_file = "audiotrack.wav"
         video_clip = VideoFileClip(mp4_file)
         audioclip = video_clip.audio
         wav_file = audioclip.write_audiofile(wav_file)
         audioclip.close()
         video_clip.close()
-        audiotrack = "results/audiotrack.wav"
+        audiotrack = "audiotrack.wav"
         result = self.whisper_model.transcribe(audiotrack, fp16=False)
         transcript = result["text"]
         print("TRANSCRIPT",transcript)
@@ -102,7 +102,7 @@ class VideoClassifier:
         time_taken_1 = round(end - start, 3)
         # print("Time taken from video to transcript:", time_taken_1)
 
-        path = './results/frames'
+        path = './frames'
         if not os.path.exists(path):
             os.mkdir(path)
         video = cv2.VideoCapture(video_input)
@@ -119,12 +119,12 @@ class VideoClassifier:
             ret,frame = video.read()
             if ret:
                 # if video is still left continue creating images
-                name = './results/frames/frame' + str(currentframe) + '.jpg'
+                name = './frames/frame' + str(currentframe) + '.jpg'
                 # writing the extracted images
                 # print ('Creating...' + name)
                 cv2.imwrite(name, frame)
                 image_paths = []
-                img_path = 'results/frames/frame' + str(currentframe) + '.jpg'
+                img_path = '/frames/frame' + str(currentframe) + '.jpg'
                 image_paths.append(img_path)
                 content = self.img_cap.predict_step(image_paths)
                 print("content",content)
@@ -144,7 +144,7 @@ class VideoClassifier:
         video.release()
         cv2.destroyAllWindows()
 
-        main_categories = Path("categories/main_classes.txt").read_text()
+        main_categories = Path("main_classes.txt").read_text()
         main_categories_list = ['Automotive', 'Books and Literature', 'Business and Finance', 'Careers', 'Education','Family and Relationships',
         'Fine Art', 'Food & Drink', 'Healthy Living', 'Hobbies & Interests', 'Home & Garden','Medical Health', 'Movies', 'Music and Audio', 
         'News and Politics', 'Personal Finance', 'Pets', 'Pop Culture','Real Estate', 'Religion & Spirituality', 'Science', 'Shopping', 'Sports', 
@@ -199,18 +199,18 @@ class VideoClassifier:
         print("POST PROCESSED MAIN CLASS : ",main_class)
         tier_1_index_no = main_categories_list.index(main_class) + 1
 
-        with open('categories/categories_json.txt') as f:
+        with open('categories_json.txt') as f:
             data = json.load(f)
         sub_categories_list = data[main_class]
         print("SUB CATEGORIES LIST",sub_categories_list)
-        with open("categories/sub_categories.txt", "w") as f:
+        with open("sub_categories.txt", "w") as f:
             no = 1
             
             # print(data[main_class])
             for i in data[main_class]:
                 f.write(str(no)+')'+str(i) + '\n')
                 no = no+1
-        sub_categories = Path("categories/sub_categories.txt").read_text()
+        sub_categories = Path("sub_categories.txt").read_text()
 
         template2 = '''Given below are the sub classes of {main_class}.
 
@@ -256,8 +256,8 @@ class VideoClassifier:
         print("ANSWER:",sub_class)
         final_answer = (f"Tier 1 category : IAB{tier_1_index_no} : {main_class}\nTier 2 category : IAB{tier_1_index_no}-{tier_2_index_no} : {sub_class}")
 
-        first_video = os.path.join(os.path.dirname(__file__), "videos/American_football_heads_to_India_clip.mp4")
-        second_video = os.path.join(os.path.dirname(__file__), "videos/PersonalFinance_clip.mp4")
+        first_video = os.path.join(os.path.dirname(__file__), "American_football_heads_to_India_clip.mp4")
+        second_video = os.path.join(os.path.dirname(__file__), "PersonalFinance_clip.mp4")
 
         # return final_answer, first_video, second_video
         return final_answer
@@ -280,10 +280,10 @@ class VideoClassifier:
         """
         demo = gr.Interface(fn=self.classify_video, inputs="playablevideo",allow_flagging='never', examples=[
                             os.path.join(os.path.dirname(__file__), 
-                                         "videos/American_football_heads_to_India_clip.mp4"),os.path.join(os.path.dirname(__file__), "videos/PersonalFinance_clip.mp4"),
-                                         os.path.join(os.path.dirname(__file__), "videos/Motorcycle_clip.mp4"),
-                                         os.path.join(os.path.dirname(__file__), "videos/Spirituality_1_clip.mp4"),
-                                         os.path.join(os.path.dirname(__file__), "videos/Science_clip.mp4")], 
+                                         "American_football_heads_to_India_clip.mp4"),os.path.join(os.path.dirname(__file__), "PersonalFinance_clip.mp4"),
+                                         os.path.join(os.path.dirname(__file__), "Motorcycle_clip.mp4"),
+                                         os.path.join(os.path.dirname(__file__), "Spirituality_1_clip.mp4"),
+                                         os.path.join(os.path.dirname(__file__), "Science_clip.mp4")], 
                         cache_examples=False, 
                         # outputs=["text", gr.Video(height=80, width=120), gr.Video(height=80, width=120)],
                         outputs=["text"],