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src/fal_api.py

@@ -1,6 +1,7 @@
 import fal_client
 from src.utils import numpy_to_base64
 from src.helpers import resize_image
+from src.deepl import detect_and_translate
 
 def fal_ipadapter_api(input_image,ip_image,seg_prompt):
   #print(input_image,ip_image,seg_prompt)
@@ -10,7 +11,7 @@ def fal_ipadapter_api(input_image,ip_image,seg_prompt):
         arguments={
             "loadimage_1":numpy_to_base64(input_image),
              "loadimage_2":numpy_to_base64(ip_image),
-            "groundingdinosamsegment (segment anything)_prompt":seg_prompt
+            "groundingdinosamsegment (segment anything)_prompt":detect_and_translate(seg_prompt)
         },
     )
   #print(handler)

src/rep_api.py

@@ -327,34 +327,25 @@ light_source_options=[
     "Ambient"
 ]
 
+defult_image="https://replicate.delivery/pbxt/KxPIbJUjSmVBlvn0M3C8PAz6brN5Z0eyZSGcKIVw3XfJ6vNV/7.webp"
 
 def replicate_iclight_BG(img,prompt,bg_img,light_source="Use Background Image",
         negative_prompt="(deformed iris, deformed pupils, semi-realistic, cgi, 3d, render, sketch, cartoon, drawing, anime, mutated hands and fingers:1.4), (deformed, distorted, disfigured:1.3), poorly drawn, bad anatomy, wrong anatomy, extra limb, missing limb, floating limbs, disconnected limbs, mutation, mutated, ugly, disgusting, amputation"
   ):
-
     assert light_source in light_source_options, "Please select a correct ligh source option"
-   #if type(img)!=str:
-   # img=open_image_from_url(img)
-   #if type(bg_img)!=str:
-   # bg_img=open_image_from_url(bg_img)
-    
     width, height = img.size
     print(width,height)
-    #print()
-    target_width = find_closest_valid_dimension(width)
-    target_height = find_closest_valid_dimension(height)
-    resized_img = resize_image(img, target_width, target_height)
-    img=image_to_base64(resized_img)
-
+    img=image_to_base64(img)
     #if light_source=="Use Background Image":
-    bg_width, bg_height = bg_img.size
-    target_width = find_closest_valid_dimension(bg_width)
-    target_height = find_closest_valid_dimension(bg_height)
-    print(bg_img)
-    bg_img = resize_image(bg_img, target_width, target_height)
+    if bg_img is None:
+      bg_img=open_image_from_url(defult_image)
     bg_img=image_to_base64(bg_img)
+    #else:
+    #bg_img=None
+
+    prompt=prompt
+
 
-  
     output=replicate.run(
        "zsxkib/ic-light-background:60015df78a8a795470da6494822982140d57b150b9ef14354e79302ff89f69e3",
     input={
@@ -371,7 +362,7 @@ def replicate_iclight_BG(img,prompt,bg_img,light_source="Use Background Image",
         "output_quality": 100,
         "appended_prompt": "best quality",
         "highres_denoise": 0.5,
-        "negative_prompt": "lowres, bad anatomy, bad hands, cropped, worst quality",
+        "negative_prompt": negative_prompt,
         "background_image": bg_img,
         "number_of_images": 1
     }

src/utils.py

@@ -10,8 +10,20 @@ import zipfile
 import numpy as np
 import json 
 import gradio as gr
+import subprocess
 
+class dwebpException(Exception):
+    pass
 
+
+def dwebp(file: str):
+    webp = subprocess.run(
+        f"dwebp {file} -quiet -o -", shell=True, capture_output=True
+    )
+    if webp.returncode != 0:
+        raise dwebpException(webp.stderr.decode())
+    else:
+        return Image.open(BytesIO(webp.stdout))
 def resize_image(img, target_width, target_height):
   """Resizes an image while maintaining aspect ratio.
 
@@ -63,9 +75,13 @@ def convert_to_pil(img):
     if isinstance(img, np.ndarray):
         img = Image.fromarray(img)
     # If the image is a URL, fetch the image and convert it to a PIL image
-    elif isinstance(img, str) and img.startswith('http'):
-        response = requests.get(img)
-        img = Image.open(BytesIO(response.content))
+    elif isinstance(img, str):
+        if "https:" in img or "http:" in img:
+          response = requests.get(img)
+          img = Image.open(BytesIO(response.content))
+        #else is pil type 
+        else:
+          img=Image.open(img)
     return img 
 
 def open_image_from_url(image_url):