1.0.20 (#35)

Re-write UI to use async codes: (1) for faster start, and (2) for better live preview.
Removed opencv dependency
Plan to support Linux soon

modules/async_worker.py

@@ -0,0 +1,77 @@
+import threading
+
+
+buffer = []
+outputs = []
+
+
+def worker():
+    global buffer, outputs
+
+    import time
+    import random
+    import modules.default_pipeline as pipeline
+    import modules.path
+
+    from PIL import Image
+    from modules.sdxl_styles import apply_style, aspect_ratios
+    from modules.util import generate_temp_filename
+
+    def handler(task):
+        prompt, negative_prompt, style_selction, performance_selction, \
+        aspect_ratios_selction, image_number, image_seed, base_model_name, refiner_model_name, \
+        l1, w1, l2, w2, l3, w3, l4, w4, l5, w5 = task
+
+        loras = [(l1, w1), (l2, w2), (l3, w3), (l4, w4), (l5, w5)]
+
+        pipeline.refresh_base_model(base_model_name)
+        pipeline.refresh_refiner_model(refiner_model_name)
+        pipeline.refresh_loras(loras)
+
+        p_txt, n_txt = apply_style(style_selction, prompt, negative_prompt)
+
+        if performance_selction == 'Speed':
+            steps = 30
+            switch = 20
+        else:
+            steps = 60
+            switch = 40
+
+        width, height = aspect_ratios[aspect_ratios_selction]
+
+        results = []
+        seed = image_seed
+        if not isinstance(seed, int) or seed < 0 or seed > 65535:
+            seed = random.randint(1, 65535)
+
+        all_steps = steps * image_number
+
+        def callback(step, x0, x, total_steps, y):
+            done_steps = i * steps + step
+            outputs.append(['preview', (
+                int(100.0 * float(done_steps) / float(all_steps)),
+                f'Step {step}/{total_steps} in the {i}-th Sampling',
+                y)])
+
+        for i in range(image_number):
+            imgs = pipeline.process(p_txt, n_txt, steps, switch, width, height, seed, callback=callback)
+
+            for x in imgs:
+                local_temp_filename = generate_temp_filename(folder=modules.path.temp_outputs_path, extension='png')
+                Image.fromarray(x).save(local_temp_filename)
+
+            seed += 1
+            results += imgs
+
+        outputs.append(['results', results])
+        return
+
+    while True:
+        time.sleep(0.01)
+        if len(buffer) > 0:
+            task = buffer.pop(0)
+            handler(task)
+    pass
+
+
+threading.Thread(target=worker, daemon=True).start()