Comment more code

app.py

@@ -94,81 +94,79 @@ class Tango:
             return outputs
         return list(self.chunks(outputs, samples))
 
-# Initialize TANGO
-
-tango = Tango(device = "cpu")
-tango.vae.to(device_type)
-tango.stft.to(device_type)
-tango.model.to(device_type)
-
-def update_seed(is_randomize_seed, seed):
-    if is_randomize_seed:
-        return random.randint(0, max_64_bit_int)
-    return seed
-
-def check(
-    prompt,
-    output_number,
-    steps,
-    guidance,
-    is_randomize_seed,
-    seed
-):
-    if prompt is None or prompt == "":
-        raise gr.Error("Please provide a prompt input.")
-    if not output_number in [1, 2, 3]:
-        raise gr.Error("Please ask for 1, 2 or 3 output files.")
-
-def update_output(output_format, output_number):
-    return [
-        gr.update(format = output_format),
-        gr.update(format = output_format, visible = (2 <= output_number)),
-        gr.update(format = output_format, visible = (output_number == 3)),
-        gr.update(visible = False)
-    ]
-
-def text2audio(
-    prompt,
-    output_number,
-    steps,
-    guidance,
-    is_randomize_seed,
-    seed
-):
-    start = time.time()
-
-    if seed is None:
-        seed = random.randint(0, max_64_bit_int)
-
-    random.seed(seed)
-    torch.manual_seed(seed)
-
-    output_wave = tango.generate(prompt, steps, guidance, output_number)
-
-    output_wave_1 = gr.make_waveform((16000, output_wave[0]))
-    output_wave_2 = gr.make_waveform((16000, output_wave[1])) if (2 <= output_number) else None
-    output_wave_3 = gr.make_waveform((16000, output_wave[2])) if (output_number == 3) else None
-
-    end = time.time()
-    secondes = int(end - start)
-    minutes = secondes // 60
-    secondes = secondes - (minutes * 60)
-    hours = minutes // 60
-    minutes = minutes - (hours * 60)
-    return [
-        output_wave_1,
-        output_wave_2,
-        output_wave_3,
-        gr.update(visible = True, value = "Start again to get a different result. The output have been generated in " + ((str(hours) + " h, ") if hours != 0 else "") + ((str(minutes) + " min, ") if hours != 0 or minutes != 0 else "") + str(secondes) + " sec.")
-    ]
-
-if is_space_imported:
-    text2audio = spaces.GPU(text2audio, duration = 420)
+## Initialize TANGO
+#
+#tango = Tango(device = "cpu")
+#tango.vae.to(device_type)
+#tango.stft.to(device_type)
+#tango.model.to(device_type)
+#
+#def update_seed(is_randomize_seed, seed):
+#    if is_randomize_seed:
+#        return random.randint(0, max_64_bit_int)
+#    return seed
+#
+#def check(
+#    prompt,
+#    output_number,
+#    steps,
+#    guidance,
+#    is_randomize_seed,
+#    seed
+#):
+#    if prompt is None or prompt == "":
+#        raise gr.Error("Please provide a prompt input.")
+#    if not output_number in [1, 2, 3]:
+#        raise gr.Error("Please ask for 1, 2 or 3 output files.")
+#
+#def update_output(output_format, output_number):
+#    return [
+#        gr.update(format = output_format),
+#        gr.update(format = output_format, visible = (2 <= output_number)),
+#        gr.update(format = output_format, visible = (output_number == 3)),
+#        gr.update(visible = False)
+#    ]
+#
+#def text2audio(
+#    prompt,
+#    output_number,
+#    steps,
+#    guidance,
+#    is_randomize_seed,
+#    seed
+#):
+#    start = time.time()
+#
+#    if seed is None:
+#        seed = random.randint(0, max_64_bit_int)
+#
+#    random.seed(seed)
+#    torch.manual_seed(seed)
+#
+#    output_wave = tango.generate(prompt, steps, guidance, output_number)
+#
+#    output_wave_1 = gr.make_waveform((16000, output_wave[0]))
+#    output_wave_2 = gr.make_waveform((16000, output_wave[1])) if (2 <= output_number) else None
+#    output_wave_3 = gr.make_waveform((16000, output_wave[2])) if (output_number == 3) else None
+#
+#    end = time.time()
+#    secondes = int(end - start)
+#    minutes = secondes // 60
+#    secondes = secondes - (minutes * 60)
+#    hours = minutes // 60
+#    minutes = minutes - (hours * 60)
+#    return [
+#        output_wave_1,
+#        output_wave_2,
+#        output_wave_3,
+#        gr.update(visible = True, value = "Start again to get a different result. The output have been generated in " + ((str(hours) + " h, ") if hours != 0 else "") + ((str(minutes) + " min, ") if hours != 0 or minutes != 0 else "") + str(secondes) + " sec.")
+#    ]
+#
+#if is_space_imported:
+#    text2audio = spaces.GPU(text2audio, duration = 420)
 
 # Old code
 net=BriaRMBG()
-# model_path = "./model1.pth"
-#model_path = hf_hub_download("briaai/RMBG-1.4", 'model.pth')
 model_path = hf_hub_download("cocktailpeanut/gbmr", 'model.pth')
 if torch.cuda.is_available():
     net.load_state_dict(torch.load(model_path))
@@ -220,36 +218,8 @@ def process(image):
     # paste the mask on the original image
     new_im = Image.new("RGBA", pil_im.size, (0,0,0,0))
     new_im.paste(orig_image, mask=pil_im)
-    # new_orig_image = orig_image.convert('RGBA')
 
     return new_im
-    # return [new_orig_image, new_im]
-
-
-# block = gr.Blocks().queue()
-
-# with block:
-#     gr.Markdown("## BRIA RMBG 1.4")
-#     gr.HTML('''
-#       <p style="margin-bottom: 10px; font-size: 94%">
-#         This is a demo for BRIA RMBG 1.4 that using
-#         <a href="https://huggingface.co/briaai/RMBG-1.4" target="_blank">BRIA RMBG-1.4 image matting model</a> as backbone. 
-#       </p>
-#     ''')
-#     with gr.Row():
-#         with gr.Column():
-#             input_image = gr.Image(sources=None, type="pil") # None for upload, ctrl+v and webcam
-#             # input_image = gr.Image(sources=None, type="numpy") # None for upload, ctrl+v and webcam
-#             run_button = gr.Button(value="Run")
-            
-#         with gr.Column():
-#             result_gallery = gr.Gallery(label='Output', show_label=False, elem_id="gallery", columns=[1], height='auto')
-#     ips = [input_image]
-#     run_button.click(fn=process, inputs=ips, outputs=[result_gallery])
-
-# block.launch(debug = True)
-
-# block = gr.Blocks().queue()
 
 gr.Markdown("## BRIA RMBG 1.4")
 gr.HTML('''
@@ -263,8 +233,6 @@ description = r"""Background removal model developed by <a href='https://BRIA.AI
 For test upload your image and wait. Read more at model card <a href='https://huggingface.co/briaai/RMBG-1.4' target='_blank'><b>briaai/RMBG-1.4</b></a>.<br>
 """
 examples = [['./input.jpg'],]
-# output = ImageSlider(position=0.5,label='Image without background', type="pil", show_download_button=True)
-# demo = gr.Interface(fn=process,inputs="image", outputs=output, examples=examples, title=title, description=description)
 demo = gr.Interface(fn=process,inputs="image", outputs="image", examples=examples, title=title, description=description)
 
 if __name__ == "__main__":