text length

app.py

@@ -40,6 +40,9 @@ def demo_predict(input_blk, text, num_samples, steps, scale, seed, show_detail):
 
     global cfgs, global_index
 
+    if len(text) < cfgs.txt_len[0] or len(text) > cfgs.txt_len[1]:
+        raise gr.Error("Illegal text length!")
+
     global_index += 1
 
     if num_samples > 1: cfgs.noise_iters = 0
@@ -51,7 +54,7 @@ def demo_predict(input_blk, text, num_samples, steps, scale, seed, show_detail):
     seed_everything(seed)
 
     sampler = init_sampling(cfgs)
-
+    
     image = input_blk["image"]
     mask = input_blk["mask"]
     image = cv2.resize(image, (cfgs.W, cfgs.H))
@@ -156,7 +159,7 @@ if __name__ == "__main__":
             with gr.Column():
 
                 input_blk = gr.Image(source='upload', tool='sketch', type="numpy", label="Input", height=512)
-                text = gr.Textbox(label="Text to render:", info="the text you want to render at the masked region")
+                text = gr.Textbox(label="Text to render: (1~12 characters)", info="the text you want to render at the masked region")
                 run_button = gr.Button(variant="primary")
 
                 with gr.Accordion("Advanced options", open=False):

configs/demo.yaml

@@ -7,6 +7,7 @@ model_cfg_path: "./configs/test/textdesign_sd_2.yaml"
 # param
 H: 512
 W: 512
+txt_len: [1, 12]
 seq_len: 12
 batch_size: 1
 

configs/test/textdesign_sd_2.yaml

@@ -104,28 +104,4 @@ model:
           attn_resolutions: []
           dropout: 0.0
         lossconfig:
-          target: torch.nn.Identity
-
-    loss_fn_config:
-      target: sgm.modules.diffusionmodules.loss.FullLoss # StandardDiffusionLoss
-      params:
-        seq_len: 12
-        kernel_size: 3
-        gaussian_sigma: 1.0
-        min_attn_size: 16
-        lambda_local_loss: 0.01
-        lambda_ocr_loss: 0.001
-        ocr_enabled: False
-
-        predictor_config:
-          target: sgm.modules.predictors.model.ParseqPredictor
-          params:
-            ckpt_path: "./checkpoints/predictors/parseq-bb5792a6.pt"
-        
-        sigma_sampler_config:
-          target: sgm.modules.diffusionmodules.sigma_sampling.DiscreteSampling
-          params:
-            num_idx: 1000
-            
-            discretization_config:
-              target: sgm.modules.diffusionmodules.discretizer.LegacyDDPMDiscretization
+          target: torch.nn.Identity