Update app.py

app.py

@@ -21,21 +21,23 @@ pipe = pipe.to("cuda")
 
 def transcribe(audio,prompt_num,user_keywords):
     
-
+    # load audio and pad/trim it to fit 30 seconds
     audio1 = whisper.load_audio(audio)
     audio1 = whisper.pad_or_trim(audio1)
 
-
+    # make log-Mel spectrogram and move to the same device as the model
     mel = whisper.log_mel_spectrogram(audio1).to(model.device)
 
-
+    # detect the spoken language
     _, probs = model.detect_language(mel)
     print(f"Detected language: {max(probs, key=probs.get)}")
 
+    # decode the audio
     options = whisper.DecodingOptions()
     result = whisper.decode(model, mel, options)
     print(result.text)
 
+    # model = whisper.load_model("base")
     audio2 = whisper.load_audio(audio)
     final_result = model.transcribe(audio2)
     print(final_result["text"])
@@ -47,6 +49,11 @@ def keywords(text,prompt_num,user_keywords):
 
     transcription = text
 
+    # ub = UrlBuilder("demo.imgix.net")
+
+
+
+
     kw_model = KeyBERT()
     a = kw_model.extract_keywords(text, keyphrase_ngram_range=(1, 3), stop_words=None)
     set_1 = [i[0] for i in a]
@@ -75,8 +82,12 @@ def keywords(text,prompt_num,user_keywords):
         my_list = user_keywords.split(',')
         print(my_list)
 
+        # for i in range(len(my_list)):
+        #   sentence.append(my_list[i])
+        
+        # numb = 5
         for i in range(len(my_list)):
-
+          # print("keyword_pool",keyword_pool, len(keyword_pool))
 
           sentence.append("mdjrny-v4 style")
           
@@ -111,10 +122,34 @@ def keywords(text,prompt_num,user_keywords):
               sentence.append(r.choice(set_3))
 
 
+          # rand1 = r.randint(0,numb)
+
+          # rand2 = r.randint(0,numb)
+          # if rand2 == rand1:
+          #   rand2 = r.randint(0,numb)
+
+          # rand3 = r.randint(0,numb)
+          # if rand3 == rand1 or rand3 == rand2:
+          #   rand3 = r.randint(0,numb)
+
+          # rand4 = r.randint(0,numb)
+          # if rand4 == rand1 or rand4 == rand2 or rand4 == rand3:  
+          #   rand4 = r.randint(0,numb)
+
+          # word_1 = keyword_pool[rand1]
+          # word_2 = keyword_pool[rand2]
+          # word_3 = keyword_pool[rand3]
+          # word_4 = keyword_pool[rand4]
+
+          # sentence.append(word_1 +", "+ word_2+", " + word_3+", " + word_4)
+
+
+                  # Add Style Tail Prompt
           sentence.append(r.choice(style_prompts))
 
           print("sentence: ", sentence)
 
+          # Formatting Data as comma-delimited for Mid Journey
           myprompt = ', '.join(str(e) for e in sentence)
           sentence = []
           print("prompt: ",myprompt)
@@ -122,18 +157,23 @@ def keywords(text,prompt_num,user_keywords):
 
           count += 1
 
+    print("no. of prompts: ", len(generated_prompts))
+    print("generated prompts: ", generated_prompts)
+
     count = 0
     images = []
-
+    # np_images = []
     while count != int(len(generated_prompts)):
+
       for i in generated_prompts:
         count += 1
+        print(i)
         image = pipe(i, height=768, width=768, guidance_scale = 10).images[0]
         images.append(image)
     
-    min_shape = sorted( [(np.sum(i.size), i.size ) for i in images])[0][1]
-    imgs_comb = np.hstack([i.resize(min_shape) for i in images])
-    imgs_comb = Image.fromarray( imgs_comb)
+    # min_shape = sorted( [(np.sum(i.size), i.size ) for i in images])[0][1]
+    # imgs_comb = np.hstack([i.resize(min_shape) for i in images])
+    # imgs_comb = Image.fromarray( imgs_comb)
     
     return images,transcription,keyword_pool,generated_prompts
 
@@ -144,8 +184,7 @@ def keywords(text,prompt_num,user_keywords):
 speech_text = gr.Interface(fn=transcribe, inputs=[gr.Audio(source="microphone", type="filepath"),gr.Number(label = "Number of Images to be generated (int): "),gr.Textbox(label = "Additional keywords (comma delimitied): ")], outputs=["text","number","text"], theme = "darkhuggingface", title = 'Speech-to-Image-Generator', enable_queue=True)
 text_prompts = gr.Interface(fn=keywords, inputs=["text","number","text"], outputs=[gr.Gallery(label="Generated images", show_label=True, elem_id="gallery").style(grid=[2], height="auto"),gr.TextArea(label="Transcription"),gr.TextArea(label="Keywords"),gr.TextArea(label="Generated Prompts")],theme = "darkhuggingface", title = 'Speech-to-Image-Generator', enable_queue=True)
 
-
 #gr.Series(speech_text,text_prompts).launch(auth = ('PWuser','speechtotextPW'), auth_message = "Welcome to Perkins&Will i/o's Synthesia Tool. Use cases: Ideation/Brainstorming tool - Have it running in the background in a conference, brainstorming session, discussion to create contextually relevant visualizations for moodboarding, to spark more conversations, interactions and inspiration. | Aprameya Pandit | February 2023 | ",inline = False, enable_queue=True).queue()
-gr.Series(speech_text,text_prompts).launch( enable_queue=True).queue()
+gr.Series(speech_text,text_prompts).launch(enable_queue=True).queue()